Progress, opportunities, and key fields for groundwater quality research under the impacts of human activities in China with a special focus on western China

Characterization and assessment of hydrological droughts using GloFAS streamflow data for the Narmada River Basin, India

Hydrological droughts severely affect the demand of water for domestic water supply, irrigation, hydropower generation, and several other purposes. The pervasiveness and consequences of hydrological droughts necessitate a thorough investigation of their characteristics, which is hindered due to unavailability of continuous streamflow records at desirable resolutions. This study aims to assess the hydrological drought characteristics and their spatial distribution using high-resolution Global Flood Awareness System (GloFAS) v3.1 streamflow data for the period 1980 to 2020. Streamflow Drought Index (SDI) was used to characterize droughts at 3-, 6-, 9-, and 12-monthly timescales starting from June, i.e., the start of water year in India. GloFAS is found to capture the spatial distribution of streamflow and its seasonal characteristics. The number of hydrological drought years over the basin varied from 5 to 11 during the study duration, implying that the basin is prone to frequent abnormal water deficits. Interestingly, the hydrological droughts are more frequent in the eastern portion of the basin, i.e., the Upper Narmada Basin. The trend analysis of multi-scalar SDI series using non-parametric Spearman's Rho test exhibited increasing drying trends in the easternmost portions. The results were not similar for the middle and western portions of the basin, which may be due to presence of a large number of reservoirs in these regions and their systematic operations. This study highlights the importance of open-access global products that can be used for monitoring hydrological droughts, especially over ungauged catchments.

Development and application of a comprehensive evaluation index system for groundwater quality evolution patterns

In recent years, driven by rapid socio-economic development and intensified human activities, the groundwater quality has exhibited a concerning trend of degradation. The challenge lies in integrating the impacts of both natural and anthropogenic factors to establish a scientific evaluation framework for the evolution of groundwater quality. This study adopts the model of driving forces - pressures - state - impacts - responses (DPSIR) proposed by the European Environment Agency, in conjunction with the Analytic Hierarchy Process (AHP) and Information Entropy Theory (IET), and the Water Quality Index (WQI) evaluation methods, to construct an evaluation index system for groundwater quality evolution that encompasses driving forces, state, and response systems. Initially, twelve indicators relevant to groundwater quality are quantified by screening across three systems, and a functional relationship between the categorization and scoring of each indicator is established. Subsequently, the weights for each system and indicator are obtained through the AHP, and the objective weights of the indicators are determined using the IET. The scores of each indicator are then comprehensively calculated. Finally, based on the defined types of groundwater quality evolution patterns, an integrated assessment of the evolution of groundwater quality over various time periods is conducted. Taking the Shijiazhuang region as a case study and analyzing the hydrochemical data of groundwater from 1985 to 2015, the results indicate a shift in the groundwater quality evolution pattern from one dominated by natural factors to one primarily influenced by human activities (The comprehensive score of the evaluation index system has increased from 1.84 to 3.25). Among these, the application of fertilizers emerges as the most important driving factors affecting groundwater quality. Particularly, nitrate and total hardness (TH) have emerged as the most salient indicators of quality degradation, with a significant escalation in their composite scores. At the outset, nitrate registered a score of 0.408, while TH scored 0.326; yet, these values have sharply ascended to 0.716 and 0.467, respectively, by the advanced stage. The study concludes with a discussion on the accuracy, strengths, limitations, and applicability of the evaluation index system. The establishment of this evaluation framework provides a scientific basis for the management and protection of groundwater resources and serves as a reference for identifying groundwater quality evolution patterns in other regions.

Geospatial interpolation and hydro-geochemical characterization of alluvial aquifers in the Thal Desert, Punjab, Pakistan

This study seeks to assess the hydrogeochemical characteristics of groundwater in the southern part of Thal Desert of Pakistan. The primary focus lies in identifying potential sources of contamination and evaluating their impact on groundwater and the ecosystem. Groundwater samples were collected from diverse sources including shallow hand pumps, tubewells, and dug wells, with depths ranging from 11 to 28 m. A comprehensive analysis was performed to scrutinize the physical, chemical, and microbial attributes of the samples. Utilizing visual aids like the Piper, Durov, and Gibbs diagrams, as well as Pearson correlation, scatter plots, Schoeller diagrams, and pie charts, the study evaluated the groundwater quality and its suitability for consumption. Results indicate that mineral infiltration from rainfall, domestic waste, and industrial effluents significantly affects groundwater quality, leading to widespread salinity. Weathering processes and ion exchange were identified as key factors contributing to elevate levels of bicarbonates, sodium, magnesium, and chloride ions. Employing the Water Quality Index (WQI) on 40 groundwater samples, findings reveal that 52.5% of samples demonstrated poor to not suitable quality, with 27.5% categorized as poor, 2.5% as very poor, and 22.5% not suitable consumption. Conversely, 47.5% of samples showcased good to excellent quality, with 25% rated as good and 22.5% as excellent. These findings provide valuable insights for hydrogeologists to develop appropriate strategies for water treatment and address any concerns related to groundwater quality.

Prediction of geogenic source of groundwater fluoride contamination in Indian states: A comparative study of different supervised machine learning algorithms

India has been dealing with fluoride contamination of groundwater for the past few decades. Long-term exposure of fluoride can cause skeletal and dental fluorosis. Therefore, an in-depth exploration of fluoride concentrations in different parts of India is desirable. This work employs machine learning algorithms to analyze the fluoride concentrations in five major affected Indian states (Andhra Pradesh, Rajasthan, Tamil Nadu, Telangana and West Bengal). A correlation matrix was used to identify appropriate predictor variables for fluoride prediction. The various algorithms used for predictions included K-nearest neighbor (KNN), logistic regression (LR), random forest (RF), support vector classifier (SVC), Gaussian NB, MLP classifier, decision tree classifier, gradient boosting classifier, voting classifier soft and voting classifier hard. The performance of these models is assessed over accuracy, precision, recall and error rate and receiver operating curve. As the dataset was skewed, the performance of models was evaluated before and after resampling. Analysis of results indicates that the RF model is the best model for predicting fluoride contamination in groundwater in Indian states.

A framework for risk assessment of groundwater contamination integrating hydrochemical, hydrogeological, and electrical resistivity tomography method

Groundwater contamination have been widely concerned. To reliably conduct risk assessment, it is essential to accurately delineate the contaminant distribution and hydrogeological condition. Electrical resistivity tomography (ERT) has become a powerful tool because of its high sensitivity to hydrochemical parameters, as well as its advantages of non-invasiveness, spatial continuity, and cost-effectiveness. However, it is still difficult to integrate hydrochemical, hydrogeological, and ERT datasets for risk assessment. In this study, we develop a general framework for risk assessment by sequentially jointing hydrochemical, hydrogeological, and ERT surveys, while establishing petrophysical relationships among these data. This framework can be used in groundwater-contaminated site and help to delineate the distribution of contaminants. In this study, it was applied to a nitrogen-contaminated site where field ERT survey and borehole information provided valuable measurement data for validating the consistency of contamination and hydrogeological condition. Risk assessment was conducted based on the refined results by the establishment of relationship between conductivity and contaminants concentration withR 2 > 0.84 . The contamination source was identified and the transport direction was predicted with the good agreement ofR 2 = 0.965 between simulated and observed groundwater head, which can help to propose measures for anti-seepage and monitoring. This study thus enhances the reliability of risk assessment and prediction through a thought-provoking innovation in the realm of groundwater environmental assessment.

Spatiotemporal assessment of groundwater quality and quantity using geostatistical and ensemble artificial intelligence tools

The study investigated the spatiotemporal relationship between surface hydrological variables and groundwater quality/quantity using geostatistical and AI tools. AI models were developed to estimate groundwater quality from ground-based measurements and remote sensing images, reducing reliance on laboratory testing. Different Kriging techniques were employed to map ground-based measurements and fill data gaps. The methodology was applied to analyze the Maragheh aquifer in northwest Iran, revealing declining groundwater quality due to industrial. discharges and over-extraction. Spatiotemporal analysis indicated a relationship between groundwater depth/quality, precipitation, and temperature. The Root Mean Square Scaled Error (RMSSE) values for all variables ranged from 0.8508 to 1.1688, indicating acceptable performance of the semivariogram models in predicting the variables. Three AI models, namely Feed-Forward Neural Networks (FFNNs), Support Vector Regression (SVR), and Adaptive Neural Fuzzy Inference System (ANFIS), predicted groundwater quality for wet (June) and dry (October) months using input variables such as groundwater depth, temperature, precipitation, Normalized Difference Vegetation Index (NDVI), and Digital Elevation Model (DEM), with Groundwater Quality Index (GWQI) as the target variable. Ensemble methods were employed to combine the outputs of these models, enhancing performance. Results showed strong predictive capabilities, with coefficient of determination values of 0.88 and 0.84 for wet and dry seasons. Ensemble models improved performance by up to 6% and 12% for wet and dry seasons, respectively, potentially advancing groundwater quality modeling in the future.

Evaluation of non-cancer risk owing to groundwater fluoride and iron in a semi-arid region near the Indo-Bangladesh international frontier

Groundwater quality in Hili, a semi-arid border region at Indo-Bangladesh border, was investigated in the post-monsoon season of 2021, succeeded by assessment of probabilistic health risk arising from fluoride (F-) and iron (Fe) intake, with the hypothesis that groundwater quality of the region was not satisfactory for human consumption and health, considering earlier reports on high groundwater F- and Fe in few of the neighboring districts. All water samples were found to be potable in terms of Ca2+, Mg2+, Cl-, SO42- and NO3-, , but F- and Fe exceeded prescribed safe limits for drinking water in about 48% and 7% samples. Almost all water samples were found to be good for irrigation in terms of sodium adsorption ratio (SAR), soluble sodium percentage (SSP), Kelly's index (KI), %Na and magnesium ratio (MR). The principal component analysis (PCA) identified three major factors influencing groundwater quality, explaining about 71.8% of total variance and indicated that groundwater quality was primarily influenced by geochemical factors. Carbonate and silicate weathering were mainly responsible for dissolution of minerals in groundwater. Non-carcinogenic risk due to cumulative impact of F-and Fe intake was in the order of THIChildren > THIInfant > THIAdult. As per Monte Carlo simulation run with 5000 trials to ascertain the order of probabilistic health risk, the most dominant governing factors behind non-carcinogenic risk caused by F-and Fe intake were their concentration (Ci) followed by ingestion rate (IR), and exposure duration (ED).

Investigating the correlation between chemical parameters, risk assessment, and sensitivity analysis of fluoride and nitrate in regional groundwater sources using Monte Carlo

Groundwater is one of the most important sources of drinking and irrigation water in arid and semi-arid areas. This study aimed to investigate the chemical quality of groundwater for drinking and irrigation, assess the non-carcinogenic risk factors resulting from the concentration of fluoride and nitrate ions, and analyze the sensitivity among children, teenagers, and adults using Monte Carlo method. A total of 171 samples were obtained from confined groundwater in Arsanjan. Among other hydrological parameters of water, EC had the highest average (1135.97). TDS ranged from 67.90 to 1878.30 mg/L, with the lowest and highest total hardness values being 2.90 and 680.8, respectively. The water quality index (WQI) results indicated that 33% of the samples were at the poor water level and the irrigation (IWQI) was less than 25 in 96.36% of the samples, which were categorized as excellent. Thus, the majority of the samples were suitable for irrigation purposes. Additionally, the oral and dermal health risks of fluoride and nitrate were less than 1 in all age groups. Concentration factor was the main indicator in the assessment of the non-carcinogenic risk factors of nitrate and fluoride. The results of sensitivity analysis revealed a reverse relationship with body weight. Further, the results of principal component analysis (PCA) showed a negative relationship between fluoride concentration and pH. Hierarchical cluster analysis also showed that the study variables belonged to three main clusters. Some elements in C1 were also found in the first factor in PCA. The elements in C2 were among the dominant compounds of the groundwater resources of the study area, which may be caused by earth cations or human activities. C3 variables may also be one of the consequences of fertilizer use in areas around groundwater sources.

Distribution characteristics, source identification and health risk assessment of trace metals in the coastal groundwater of Taizhou City, China

This study was carried out to evaluate and analyze the fluctuations in groundwater for certain trace metals (Fe, Mn, Cu, Zn, Al, Cd, Cr, Pb, As, and Se) in Taizhou City over three years (2020-2022), evaluate the potential human health risks due to the consumption of groundwater. To quantify the spatiotemporal changes in groundwater trace metals, the heavy metal pollution index (HPI) and heavy metal evaluation index (HEI) were utilized. Furthermore, multivariate statistical methods were utilized to distinguish the sources of trace elements. Deterministic health risk assessment and Monte Carlo health risk simulation methods were employed to evaluate human health risks associated with exposure to trace metals. The results indicate that areas with higher pollution are in the south-central region, with low HPI increasing from 50% to 75% and low HEI from 68.75% to 81.25%, reflecting improved water quality. Correlation matrix analysis and principal component analysis (PCA) pinpointed anthropogenic sources as major trace metal contributors. Cr and As concentrations were associated with farming activities, Cd and Pb concentrations showed links to local industries such as e-waste recycling and shipbuilding. Furthermore, Cu levels in groundwater was influenced by the combined effects of industry, agriculture, and urban sewage discharge. Based on the hazard quotient (HQ) and hazard index (HI) calculations, the majority of groundwater samples did not exceed the reference values, indicating acceptable noncarcinogenic risks for both adults and children. However, the analysis of carcinogenic risk (CR) and uncertainty revealed an overall decreasing trend in carcinogenic risk, with Cr and Cd possessing the highest potential for causing carcinogenic risks. The sensitivities were 46.3%, 53.3%, and 70.3% for Cr, and 18.8%, 27.6%, and 9.3% for Cd.

Enhancing groundwater management using aggregated-data analysis and segmented robust regression: A case study on spatiotemporal changes in water quality

Groundwater quality management, crucial for ensuring sustainable water resources and public health, is the scope of this study. Our objective is to demonstrate the significance of secondary data analysis for the spatiotemporal characterization of groundwater quality. To this end, we develop and employ a robust trend analysis method, in tandem with a spatiotemporal data aggregation method, to accurately identify shifts in groundwater quality over time, even in the face of inflection points or breakpoints. The methods and results reveal diverse trends and characteristics in water quality over space and time across the entire dataset from selected regions in South Korea, emphasizing the importance of analyzing aggregated data beyond individual business locations. The conclusions indicate that this study contributes to the development of more reliable and effective groundwater quality management strategies by addressing gaps in traditional monitoring methods and the challenges of limited monitoring resources and uneven data quality. Future research directions include the application of the developed methods to other regions and data sources, opening avenues for further advances in groundwater quality management.

Evolution and attribution of ecological flow in the Xiangjiang River basin since 1961

Climate change and human activities have greatly altered the ecological flow of rivers, and the conflict between human water use and natural water demand is becoming more and more prominent. Using two ecological flow indicators (ecodeficit and ecosurplus), this study focuses on assessing the characteristics of ecological flow changes at multiple time scales and introduces the Long Short-Term Memory model to construct a meteorological streamflow model for the Xiangjiang River (XJR) basin, using a separation framework to quantify the effects of human disturbance and climate change on ecological flow at multiple time scales. In addition, the fluvial biodiversity Shannon Index (SI) was used to assess the response processes of riverine ecosystems under changing conditions. The results show that the increase of XJR flow is larger (11%) after 1991, the increase in precipitation and potential evapotranspiration in the basin is 5.60%, and the decrease is 3.09%, respectively, and there are obvious cycles of all three on annual and seasonal scales. The annual ecosurplus increased, and the annual ecodeficit decreased after the hydrological variation; on the seasonal scale, the ecodeficit decreased significantly in summer and autumn, and the ecosurplus increased substantially in winter. Climatic factors were the main drivers of the increased frequency and magnitude of annual, summer, and fall high flows (91%, 94%, and 65% contributions, respectively), while urbanization expansion and reservoir diversions drove the increase in spring ecodeficit. Changes in river flow maintained the ecosurplus at a low level after 2002, further causing a decrease in river biodiversity, and the annual and summer ecosurplus were highly correlated with SI indicators (0.824 and 0.711, respectively). Our study contributes to the development of effective ecological flow regulation policies for the XJR basin.

Land use dynamics and its influences on groundwater depth levels in South region of National Capital Territory (NCT) of Delhi, India

The present study envisions the influences of land use dynamics on the spatial trend of groundwater depth levels over a period of two decades in the south region of NCT Delhi, India. The findings have inferred that among five major LULC categories, built-up has shown a sprawling trend (+2.17 km2/year) from the north, northeastern, and central portions to the confined patches observed in the south and southwest fringes of South Delhi from 2001 to 2021. Likewise, vegetation class has also witnessed significant increment (+1.91 km2/year) to the peripheral boundary, i.e., southern, southwest/eastern fringes, and central portions under recent initiatives of city forests, plantation drives, and urban green spaces programs. On the contrary, a negative rate of change has been observed in fallow land (-2.78 km2/year), agriculture (-1.22 km2/year), and water bodies (-0.07 km2/year). LULC transition matrix has also showed prominent conversion of fallow land into vegetation and built-up class, and change of vegetation into built-up, and fallow land category. Subsequently, corresponding LULC maps have been superimposed with long-term trends of groundwater depth levels (as spatial contours). For entire South Delhi region, depth to water levels ranged from 2.02 to 66.45 meters below ground level (mbgl) where shallower depths followed a negative trend and remain persistent throughout the time period in north and northeastern fringes. Higher fluctuations in groundwater depletion with positive trends directly get influenced with allied land use transitions such as a steady increase in built-up area and steeper depth levels (> 40 mbgl) as observed in central, southwestern, and southern parts. Moreover, buffer peripheries in the proximity of groundwater monitoring stations viz., Hauz Khas, Pushp Vihar, Jamali, Gadaipur, and Bhatti Kalan have observed deeper groundwater levels allied to built-up expansion. Thus, groundwater depletion trends can be ascribed to the incessant conversion of recharging areas into impervious zones along with uneven distribution of groundwater usage and supply. Conversely, expanding vegetative land has also shown improved groundwater depth levels. Therefore, land use influences must be managed in the long run for ensuring sustainable management of groundwater resources.

A critical application of different methods for the vulnerability assessment of shallow aquifers in Zhengzhou City

Groundwater vulnerability can partially reflect the possibility of groundwater contamination, which is crucial for ensuring human health and a good ecological environment. The current study seeks to assess the groundwater vulnerability of Zhengzhou City by adopting an amended version of the traditional DRASTIC model, i.e., the DRASTICL model, which incorporates land use type indicators. More specifically, the AHP-DRASTICL, entropy-DRASTICL, and AE-DRASTICL models were established by optimizing weights using the analytic hierarchy process (AHP) and entropy weight method. The evaluation results for these five models were divided into five levels: very low, low, medium, high, and very high. Using Spearman's rank correlation coefficient, the nitrate concentration was used to verify the groundwater vulnerability assessment results. The AE-DRASTICL model was found to perform the best, with a Spearman correlation coefficient of 0.78. However, the AHP and entropy weight method effectively improved the accuracy of vulnerability assessment results, making it more suitable for the study area. This study provides important insights to inform the design of strategies to protect groundwater in Zhengzhou.

Spatial variation in groundwater quality and health risk assessment for fluoride and nitrate in Chhotanagpur Plateau, India

The evaluation of groundwater quality is vital to assess the risk to human health. The present study assesses groundwater quality for drinking purposes and human health risks due to ingestion of fluoride and nitrate through drinking water in Chhotanagpur Plateau, India, using geoinformation techniques. For drinking water quality assessment, analyzed parameters were compared with World Health Organization (WHO) standards, and water quality index (WQI) was used. Results reveal that most of the samples come within the desired limit suggested by WHO. In a few samples, conductivity, hardness, chloride, sulfate, and calcium are higher than the desirable limit, whereas fluoride and nitrate are beyond the permissible limit in 70% and 27% of the samples, respectively. WQI highlights that poor to very poor water is present in 25% of the samples. Anthropogenic activities have played a critical role in deteriorating groundwater quality, resulting in harmful impacts on human health. To assess non-carcinogenic health risks, the hazard quotient (HQ) and total hazard index (THI) were computed. THI ranges from 0.01 to 7.46, 0.01 to 7.05, and 0.01 to 9.05 for males, females, and children, respectively. THI is greater than the allowable limit in 84%, 78%, and 89% of the samples for males, females, and children, respectively, indicating high risk to human health, particularly children. The study advocates proper water management strategies. Knowledge of spatial variation and anomalous concentration is vital for groundwater management as well as health risk assessment. The findings of this study will be helpful to government officials, policy planners, and local communities.

Using the colour of recent overbank sediment deposits in two large catchments to determine sediment sources for targeting mitigation of catchment-specific management issues

The effective management of sediment losses in large river systems is essential for maintaining the water resources and ecosystem services they provide. However, budgetary, and logistical constraints often mean that the understanding of catchment sediment dynamics necessary to deliver targeted management is unavailable. This study trials the collection of accessible recently deposited overbank sediment and the measurement of its colour using an office document scanner to identify the evolution of sediment sources rapidly and inexpensively in two large river catchments in the UK. The River Wye catchment has experienced significant clean-up costs associated with post-flood fine sediment deposits in both rural and urban areas. In the River South Tyne, fine sand is fouling potable water extraction and fine silts degrade salmonid spawning habitats. In both catchments, samples of recently deposited overbank sediment were collected, fractionated to either <25 μm or 63-250 μm, and treated with hydrogen peroxide to remove organic matter before colour measurement. In the River Wye catchment, an increased contribution from sources over the geological units present in a downstream direction was identified and was attributed to an increasing proportion of arable land. Numerous tributaries draining different geologies allowed for overbank sediment to characterise material on this basis. In the River South Tyne catchment, a downstream change in sediment source was initially found. The River East Allen was identified as a representative and practical tributary sub-catchment for further investigation. The collection of samples of channel bank material and topsoils therein allowed channel banks to be identified as the dominant sediment source with an increasing but small contribution from topsoils in a downstream direction. In both study catchments, the colour of overbank sediments could quickly and inexpensively inform the improved targeting of catchment management measures.

Machine learning approach to evaluate the groundwater quality and human health risk for sustainable drinking and irrigation purposes in South India

The main purpose of this study was to evaluate the suitability of groundwater for sustainable drinking and irrigation purposes using various indices, such as the nitrate pollution index, agriculture suitability index (ASI), non-carcinogenic human risk assessment (NCHRA), and radial basic function (RBF) model. The novelty of the present study is to develop the ASI model and integrate with RBF model to identify the highly dominating parameter in chemical equilibrium of groundwater. Results showed that >85% of sample locations were suitable for drinking purposes, and the nitrate concentration in groundwater had a negative impact on the overall quality of water. Approximately 12 and 19 sample locations were contaminated owing to the high nitrate concentrations in the study region. The NCHRA study identified that approximately 8.5%, 27.28%, 29.54%, 40.40%, and 28.20% of area was excessively affected during the winter compared to summer season for people 6 to 12 y, 13 to 19 y, 20 to 29 y, 30 to 65 y, and >65 y of age. The RBF model shows that the R² values for each season were 0.84 and 0.85 during summer and winter, respectively. The north-east and central parts of the study region were found to be more contaminated. The present study identified that, pathway of nitrate contaminant from the agriculture field towards to the sample locations. Overall, parent rock weathering, carbonate ion dissolution, and infiltration of rainwater and leachate from municipal waste dumping yards were the dominant factors influencing the chemical composition of groundwater. The present study achieved the vibrant knowledge about source of contamination, health effect on human body and impact on agriculture uses to develop the cleaner water supply system. The study results will be helpful in enhancing the sustainable action plan for water management in the study area.

Adverse health and environmental outcomes of sewage treatment plant on surrounding groundwater with emphasis on some mitigation recommendations

Water quality deterioration hinders economic and social development in developing countries that are facing freshwater security and shortages. Based on the collection of 29 water samples, this study focused on the relationship between sewage treatment plant and groundwater system surrounding it using multidisciplinary approach that combines the characterization of groundwater system and its connection with surrounding canal and drains, using chemical and isotopic characterization revealing that there is a direct relation between the surface water system and surrounding groundwater system. About 58% of the groundwater samples and all surface water samples in the investigated area are threatened by high concentrations of trace elements. The multivariate statistical analysis elucidates that anthropogenic effect and fertilizers sewage contamination are the main causes of groundwater pollution. Nearly, 31% and 11.5% of groundwater samples were posing oral chronic non-carcinogenic health risk and dermal chronic risk for adult, respectively, while all surface water samples were posing oral chronic non-carcinogenic health risk, with no dermal hazard. The uncharged species of Fe and Al are expected to be more mobile in groundwater because they would not be attracted to the surface charge of minerals. Inorganic ligands (HCO₃^-, SO₄^2-, Cl^-, and NO₃^-) act as nucleation centers that were linked with those trace elements creating new species with higher solubility degree in water that are transported away randomly for long distances in the water path.

The impact of two insecticides on the pollutant cycle and quality of surface and groundwater resources in the irrigated lands of Yasuj, Iran

The increase in the need for food and agricultural development has led to an increase in the use of insecticides. The use of insecticides leads to air, soil and water pollution. This study investigated the pollutant concentration cycle in the environment by analyzing diazinon and deltamethrin in a river and groundwater sources affected by an agricultural area. The samples were analyzed based on the standard method for insecticides in water using a GC-MS. The results showed that the quality of the surface water affected by the agricultural effluents decreased so that the changes of dissolved oxygen, nitrate, turbidity, TOC, BOD, and COD were 15.2%, 189.6%, 00%, 53%, 176%, and 57.5%, respectively. The concentration of diazinon and deltamethrin in agricultural wastewater was 86 μg/L and 11.62 μg/L. The self-treatment capacity of the river reduced the concentration of diazinon in the distance of 2 km and 15 km by 80.8% and 90.3%, respectively. These conditions were observed for deltamethrin in 74.8% and 96.2%, respectively. Also, the concentration of the two insecticides in water resources has temporal and spatial variation. The difference between the maximum and minimum concentration of diazinon and deltamethrin at different times was 183.5 and 1.73, respectively. The concentration of diazinon and deltamethrin in the downstream groundwater of the studied irrigated area was 0.3-0.7 μg/L, respectively. Although the soil structure and the self-purification capacity of the river caused a significant reduction of insecticides, the remained concentration of these pollutants in underground and surface water resources can still be a health and environmental concern.

A multi-model study for understanding the contamination mechanisms, toxicity and health risks of hardness, sulfate, and nitrate in natural water resources

Several water quality contaminants have attracted the attention of numerous researchers globally, in recent times. Although the toxicity and health risk assessments of sulfate and water hardness have not received obvious attention, nitrate contamination has gained peculiar research interest globally. In the present paper, multiple data-driven indexical, graphical, and soft computational models were integrated for a detailed assessment and predictive modeling of the contamination mechanisms, toxicity, and human health risks of natural waters in Southeast Nigeria. Majority of the tested physicochemical parameters were within their satisfactory limits for drinking and other purposes. However, total hardness (TH), SO₄, and NO₃ were above stipulated limits in some locations. A nitrate health risk assessment revealed that certain areas present a chronic health risk to children, females, and males due to water intake. However, the dermal absorption route was found to have negligible health risks. SO₄ in some locations was above the 100 mg/L Nigerian limit; thus, heightening the potential health effects due to intake of the contaminated water resources. Most samples had low TH values, which exposes users to health defects. There are mixed contamination mechanisms in the area, according to graphical plots, R-mode hierarchical dendrogram, factor analysis, and stoichiometry. However, geogenic mechanisms predominate over human-related mechanisms. Based on the results, a composite diagrammatic model was developed. Furthermore, predictive radial basis function (RBF) and multiple linear regression (MLR) models accurately predicted the TH, SO₄, and NO₃, with the RBF outperforming the MLR models. Insights from the RBF and MLR models were useful in validating the results of the hierarchical dendrogram, factor, stoichiometric, and graphical analyses.

Spatial evolution analysis of groundwater chemistry, quality, and fluoride health risk in southern Hebei Plain, China

The present study investigated ion and fluoride concentrations in groundwater and their associated health risks to local populations in the southern Hebei Plain during 2018-2020. A total of 336 groundwater samples were collected from monitoring wells at 112 different locations. Statistical analysis, Gibbs diagram, principal ion ratio, and saturation index were carried out to clarify the chemical characteristics and control mechanism of groundwater. The results indicated that the groundwater types in the study area were mainly HCO₃-Ca, Cl-Na, and SO₄-Ca. The concentrations of cations and anions were Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ and HCO₃^- > SO₄^2- > Cl^- > NO₃^- > F^-, respectively. Based on the water chemical parameters, the pollution index of groundwater (PIG) was used to comprehensively evaluate the water quality. The results showed that during the study period, 60.41% of groundwater samples were suitable for drinking purposes, and 39.59% needed purification treatment to meet the requirements of drinking water standards. The groundwater quality in the western pre-hill plain areas was good, while the water quality in the northeastern and southeastern areas was poor and contaminated to varying degrees. Groundwater quality was mainly affected by the combined effect of total dissolved solids (TDS), Na⁺, Mg²⁺, Cl^-, SO₄^2- and HCO₃^- concentrations. Fluoride concentrations in the groundwater samples ranged from 0.07 to 8.51 mg/L, with 44% of the samples containing fluoride below the recommended limit of 0.5 mg/L, which would put the population at risk of dental caries. Also, 8% of the samples exceeded the permissible limit for fluoride in drinking water (1.5 mg/L), which would expose the local population to the risk of fluorosis. The human health risk evaluation of fluoride showed significant differences in non-carcinogenic effects between two different groups of children and adults. HI_in values ranged from 0.08 to 10.19 for children and 0.03 to 4.65 for adults, with hazard indices greater than 1 at 29.16% and 10.11%, respectively. This indicates that children have a greater exposure risk than adults, and the entropy of higher risk is mainly distributed in the northeast of the study area. Based on the above analysis of the spatial evolution of groundwater chemistry, water quality, and fluoride health risks in the southern Hebei Plain region, corresponding protection and management measures were proposed, which also provided reference significance for the effective use of drinking water and health risk prevention in the region.

Evaluation of machine learning algorithms for groundwater quality modeling

Groundwater quality is typically measured through water sampling and lab analysis. The field-based measurements are costly and time-consuming when applied over a large domain. In this study, we developed a machine learning-based framework to map groundwater quality in an unconfined aquifer in the north of Iran. Groundwater samples were provided from 248 monitoring wells across the region. The groundwater quality index (GWQI) in each well was measured and classified into four classes: very poor, poor, good, and excellent, according to their cut-off values. Factors affecting groundwater quality, including distance to industrial centers, distance to residential areas, population density, aquifer transmissivity, precipitation, evaporation, geology, and elevation, were identified and prepared in the GIS environment. Six machine learning classifiers, including extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), artificial neural networks (ANN), k-nearest neighbor (KNN), and Gaussian classifier model (GCM), were used to establish relationships between GWQI and its controlling factors. The algorithms were evaluated using the receiver operating characteristic curve (ROC) and statistical efficiencies (overall accuracy, precision, recall, and F-1 score). Accuracy assessment showed that ML algorithms provided high accuracy in predicting groundwater quality. However, RF was selected as the optimum model given its higher accuracy (overall accuracy, precision, and recall = 0.92; ROC = 0.95). The trained RF model was used to map GWQI classes across the entire region. Results showed that the poor GWQI class is dominant in the study area (covering 66% of the study area), followed by good (19% of the area), very poor (14% of the area), and excellent (< 1% of the area) classes. An area of very poor GWQI was observed in the north. Feature analysis indicated that the distance to industrial locations is the main factor affecting groundwater quality in the region. The study provides a cost-effective methodology in groundwater quality modeling that can be duplicated in other regions with similar hydrological and geological settings.

Evaluating groundwater nitrate and other physicochemical parameters of the arid and semi-arid district of DI Khan by multivariate statistical analysis

Nitrate as an important water pollutant, causing eutrophication was analyzed in Pakistan at different water sources (hand pump (HP), bore hole (BH) and tube well (TW)) to assess the contamination level caused by NO₃^-. NO₃^- concentrations in the HP water samples were 31 mg L^-1 to 59 mg L^-1, in BH 20 mg L^-1 to 79 mg L^-1 while in TW water samples it was between 29 to 55 mg L^-1. The association of NO₃^- with other selected parameter in groundwater can be determined by using statistical approaches. Different physicochemical parameters (pH, electrical conductivity (EC), temperature and dissolved oxygen (DO)) were studied in groundwater samples of the research district. The Pearson correlation coefficient (r) for groundwater characteristics were calculated. Hierarchical Cluster Analysis (HCA) was used to categorize samples based on their groundwater quality similarities and to find links between groundwater quality factors. The key relationship of the groundwater for HP samples on EC and TDS (r = 1) had a great correlation, while all other parameters correlations were lower (r = 0.40), BH's parameters on WT and WSD (r = 0.57), WT and pH (r = 0.57), EC and DO (r = 0.50), DO and TDS (0.50), EC and TDS (r = 1) had a quite high correlation, while all other parameters correlations were less than (r = 0.40), on the other hand, tube well parameters on TDS and EC (r = 1) had a perfect correlation, DO and pH (r = 0.75) parameters correlations were less than (r = 0.40).

Hydrochemistry, Sources and Management of Fracturing Flowback Fluid in Tight Sandstone Gasfield in Sulige Gasfield (China)

Hydraulic fracturing technologies have been frequently utilized in the oil and gas industry as exploration and development efforts have progressed, resulting in a significant increase in the extraction of natural gas and petroleum from low-permeability reservoirs. However, hydraulic fracturing requires a large amount of freshwater, and the process results in the production of large volumes of flowback water along with natural gas. In this study, three tight sandstone gas wells were fractured in the Sulige gasfield (China), and a total of 103 flowback fluid samples were collected. The hydrochemical characteristics, water quality and sources of hydrochemical components in the flowback fluid were discussed. The results show that the flowback fluid is characterized by high salinity (Total dissolved solids (TDS) up to 38,268 mg/L, Cl^- up to 24,000 mg/L), high concentrations of metal ions (e.g., Fe, Sr²⁺, Ba²⁺) and high chemical oxygen demand (COD). The flowback fluid is a complex mixture of fracturing fluid and formation water, and its composition is impacted by water-rock interactions that occur during hydraulic fracturing. The major contaminants include COD, Fe, Ba²⁺, Cl^-, Mn and pH, which constitute a high risk of environmental pollution. Meanwhile, chemical elements such as K, Ba and Sr are unusually enriched in the flowback fluid, which has an excellent potential for recycle of chemical elements. The Sulige gasfield's flowback fluid recovery methods and treatment scenarios were discussed, taking into consideration the pollution and resource characteristics of the flowback fluid. Options for dealing with the flowback fluid include deep well reinjection, reuse for making up fracturing fluid, recycling of chemical elements and diverse reuse of flowback water. This research offers guidance for managing the fracturing flowback fluid in unconventional oil and gas fields.

Construction of heterotrophic-sulfur autotrophic integrated fluidized bed reactor for simultaneous and efficient removal of compound pollution of perchlorate and nitrate in water

A heterotrophic sulfur autotrophic integrated fluidized bed reactor was established for simultaneous and efficient removal of ClO₄^- and NO₃^- from water. The optimum operating conditions forecasted through the response surface method (RSM) were the hydraulic retention time (HRT) of 0.50 h, the influent acetate (CH₃COO^-) concentration of 55 mg/L and the reflux ratio of 14, contributing to ClO₄^- and NO₃^- removal of 98.99% and 99.96%, respectively, without secondary pollution caused by residual carbon (NPOC <3.89 mg/L). Meanwhile, the effluent pH fluctuated in a range of 6.70-8.02 and sulfur-containing by-products (i.e., SO₄^2- and S^2-) could be controlled by adjusting operation conditions throughout the experimental stage. The increase of the influent CH₃COO^- concentration reduced the load borne by autotrophic reduction process and further reduced SO₄^2- production. Shortening HRT, increasing the influent CH₃COO^- concentration and decreasing the reflux ratio could all reduce alkalinity consumption. Shortening HRT and decreasing the reflux ratio could shorten contact time between sulfur and water and thus inhibit S⁰ disproportionation. High-throughput sequencing result showed that Proteobacteria and Chlorobi were the dominant bacteria. Sulfurovum, Sulfuricurvum and Ignavibacterium were the major heterotrophic denitrifying bacteria (DB)/perchlorate reducing bacteria (PRB), Ferritrophicum and Geothrix were DB, and Chlorobaculum was S⁰ disproportionation bacteria.

Variation and multi-time series prediction of total hardness in groundwater of the Guanzhong Plain (China) using grey Markov model

Total hardness (TH) is an important index representing the water suitability for domestic purpose. TH is represented mainly by Ca²⁺ and Mg²⁺ which are essential elements for human bone development. Between 2000 and 2015, the TH values of groundwater in major cities of the Guanzhong Plain varied significantly. The study was carried out to investigate TH variation over 16 years and to examine how effective the grey Markov model was in predicting TH concentrations in time series datasets. The hydrochemical parameters determining TH concentration and their origins were investigated using statistical analysis and geochemical models. The grey Markov model, which is effective in short time series prediction, was used to forecast the multi-time series of TH. The findings demonstrated a prevalence of HCO₃^- and SO₄^2- in the groundwater types combined with calcite precipitation, gypsum, and dolomite dissolution that increased the concentration of Ca²⁺, Mg²⁺, and HCO₃^-, influencing TH variation. The predicted TH values of the eight monitoring wells for the year 2016 were 1213.66, 124.30, 203.66, 103.01, 349.56, 251.23, 453.31, and 471.81 mg/L, respectively. Datasets with low TH variation were more accurately predicted than datasets with high TH variation. This was especially observed on sample B557 where TH concentration in 2010 was 400.33 mg/L and suddenly dropped to 90.1, 82.6, 85.1, 87.6, and 75.1 mg/L in 2011, 2012, 2013, 2014, and 2015, respectively. The study also shows that the Markov chain model can optimize the GM(1,1) model and improve the prediction accuracy significantly. All samples in Weinan City and one sample in Xi'an City showed a significant decrease in TH concentration. Except one sample in Xi'an City, TH concentrations tended to rise in the other cities (Baoji, Xianyang) of the Guanzhong Plain. This study verified the reliability of the grey Markov model in terms of forecasting time series datasets with high variability, and the results can be referential to similar studies in the world.

Awareness Level of Business Students regarding Drinking Water Safety and Associated Adulteration Accidents: A Multinomial Logistic Regression Approach

The industrialization of metropolis urban areas with dry and steppe climates raise substantial environmental contamination, particularly in the water domain. This research investigated the awareness levels of business students toward drinking water quality and safety. We further explored the knowledge of the business students regarding drinking water issues and remedies. Eighty-four percent of respondents were happy with the quality of their drinking water, according to the findings. Approximately 66% of respondents paid special or rather high attention to drinking water quality and contamination incidents, particularly regarding possible harm to the human body and health, impact scope, and accident reasons. Few respondents reported to the health department or phoned the water safety department; 47.5% of respondents resolved drinking water issues independently. Age and education level did not play a significant role in the degree of public satisfaction with water quality or the public's perception of water pollution incidents; however, business students in Samundri were more satisfied with their drinking water quality, and residents of Faisalabad Sadar were more aware of drinking water contamination incidents than residents in areas without such a network. Respondents with higher levels of education were more aware of water quality and pollution incidents than those with lower levels of education. The steppe climate, diverse human activities, and industrialization led to water pollution. The current research findings may provide fundamental data for efficient water management in the most populated and industrialized regions.

Chemical Toxicants in Water: A GeoHealth Perspective in the Context of Climate Change

The editorial focuses on four major themes contextualized in a virtual GeoHealth workshop that occurred from June 14 to 16, 2021. Topics in that workshop included drinking water and chronic chemical exposure, environmental injustice, public health and drinking water policy, and the fate, transport, and human impact of aqueous contaminants in the context of climate change. The intent of the workshop was to further define the field of GeoHealth. This workshop emphasized on chemical toxicants that drive human health. The major calls for action emerged from the workshop include enhancing community engagement, advocating for equity and justice, and training the next generation.

Key Factors Dominating the Groundwater Chemical Composition in a Grain Production Base: A Case Study of Muling–Xingkai Plain, Northeast China

Groundwater quality in the Muling–Xingkai Plain (MXP) is closely related to food security and human health. The chemical composition of groundwater in MXP has attracted great attention. A total of 168 groundwater samples were collected in MXP, and principal component analysis, chemical ion analysis and stable isotopic analysis were used to explore key factors affecting the chemical composition and hydrochemical evolution process of groundwater. Results show sources of chemical ions in groundwater are silicate minerals, carbonate minerals and domestic sewage. Domestic sewage is responsible for groundwater with high levels of Cl−, SO42− and NO3−, but a reduction environment can lead to groundwater with a high level of NH4+ due to nitrification. Human activity and soil media together influence groundwater chemical composition. Groundwater with a high level of chemical ions is mainly collected from wells near river channels, where coarse-textured soils are overlying aquifers. The black soil far away from river channels can retard the infiltration of wastewater. Agricultural activities do not directly lead to deterioration of groundwater qualities, and agricultural non-point-source pollution does not occur in MXP. Nearly 70% of the population in MXP is living in the southern plain, where the influence of sewage on groundwater chemical composition is obvious. Thus, shallow groundwater far away from river channels is the best choice for irrigation. Some measures should be implemented to control the discharge of domestic sewage for the protection of groundwater. In addition, it is necessary to avoid the transformation of the redox environment of groundwater in the northern plain.

Characterisation of Hydro-Geochemical Processes Influencing Groundwater Quality in Rural Areas: A Case Study of Soutpansberg Region, Limpopo Province, South Africa

Groundwater is often the main or only source of fresh water supply in arid to semi-arid rural areas owing to decreasing rainfall patterns, reduced availability of surface water and socioeconomic activities. It is important to understand the hydro-geochemical processes influencing groundwater quality for improved management and sustainability of resources and to improve rural livelihoods. To understand the hydro-geochemical process influencing the hydro-geochemistry of the Soutpansberg region, this study assessed groundwater quality data from 12 boreholes and 2 geothermal springs collected between 1995 and 2017. This study indicated that the majority of the samples were classified as fresh groundwater dominated by Ca-HCO3 and mixed Ca-Mg-Cl types. Gibbs diagrams, Pearson correlations, bivariate plots and saturation indexes suggested that rock dominance processes, such as weathering of silicates, dissolution of carbonates and halite minerals and ion exchange processes, were the main hydro-geochemical processes influencing the groundwater quality in the Soutpansberg region. The high concentration of F− in the geothermal spring was attributed to the dissolution of fluorite mineral. Point source anthropogenic inputs from fertilisers were attributed to the high concentration of NO3− in the groundwater. This study recommends that research outputs should be used to influence and support policy change and groundwater allocation in arid to semi-arid rural environments for improved management of resources and livelihoods. This study further recommends that suitable deflouridation and denitrification techniques be applied to improve the quality of groundwater for drinking purposes.

Characterization of drinking groundwater quality in rural areas of Inner Mongolia and assessment of human health risks

Groundwater is an important natural resource of drinking water in rural areas in Inner Mongolia, China. In this study, 4438 drinking groundwater samples were collected from the rural areas of 81 counties in Inner Mongolia, and were analyzed for 16 parameters, including pH, total hardness (TH), chemical oxygen demand (COD), total dissolved solids (TDS), sulfate (SO42-), chloride (Cl-), fluoride (F-), iron (Fe), manganese (Mn), arsenic (As), cadmium (Cd), hexavalent chromium (Cr), lead (Pb), aluminum (Al), cuprum (Cu), zinc (Zn). The groundwater quality was evaluated with water quality index (WQI) and human health risk assessment (HRA). Monte Carlo simulation were applied for the uncertainty and sensitivity analysis in the health risk assessment. The spatial map was employed based on the inverse distance weighted (IDW) interpolation technique. The results reveal that while the hazard quotient (HQ) suggests that the risk of single element contamination is feeble, the hazard index (HI) indicates a potential health risk for the local population. The observed cumulative carcinogenic risk (CCR) indicates a probable risks of carcinogenic health hazards in the study area. The sensitivity analysis revealed that daily ingestion rate (IR), exposure frequency (EF), and the concentrations of As, Mn, F-, and Cr are the most influential parameters for health hazards. The highly polluted areas are mainly distributed in the central and western regions of Inner Mongolia, including Xianghuangqi, New Barag Zuoqi, and Togtoh. It is observed that the groundwater may cause a potential health risk after long-term ingestion. The results of this study will contribute to groundwater management and protection in Inner Mongolia.

Influence of Urbanization on Groundwater Chemistry at Lanzhou Valley Basin in China

With the rapid development of the economy, urbanization and industrialization gradually become an important driving force of groundwater chemical evolution. In this study, Lanzhou City, which is one of the biggest industrial cities in northwest China, was selected to investigate the impacts of city development on groundwater quality. Several hydrochemical methods together with principal component analysis (PCA) were used for the hydrochemistry evolution characteristics and sensitive factors of groundwater chemistry in different urban functional areas of Lanzhou City. The results show that 96% of the groundwater in the study area cannot meet the groundwater quality standards of China. The main factors affecting the quality are SO42−, TDS, total hardness, Mg2+ and Na+. Urbanization and industrialization lead to further deterioration of the already naturally high TDS groundwater. NO3−, Cl− and NH4+ are the characteristic factors of human input sources for commercial residential areas; total Fe and NO3− are the characteristic factors of new urban areas in the urban-rural junction; and SO42−, NO3−, Cl−, Total Fe, Mn2+, F−, I−, Pb2+, Cr6+ and As3+ are the characteristic factors of industrial areas. Domestic sewage infiltration and manure infiltration are the main driving factors of groundwater quality deterioration in commercial residential areas. Nitrate fertilizer infiltration and sewage irrigation are the main factors leading to the increase in nitrate nitrogen in groundwater in the new urban area. Industrial wastewater leakage and organic pollution that promote the dissolution of minerals in the aquifer (the dissolution of fluorine-containing minerals and reductive dissolution of iron manganese oxides) are the main driving factors for the deterioration of groundwater quality in the petrochemical industrial area.

Groundwater contamination risk assessment using a modified DRATICL model and pollution loading: A case study in the Guanzhong Basin of China

Groundwater contamination risk assessment is not only the basis for groundwater management, but also an effective tool for groundwater pollution control and prevention. However, only groundwater vulnerability assessment is not enough to prove the risk of groundwater contamination. Therefore, this study describes an evaluation method combining aquifer intrinsic vulnerability and pollution source loading to evaluate groundwater contamination risk in Guanzhong Basin on a macro scale. A modified DRATICL model was introduced to evaluate the intrinsic vulnerability, and the analytic hierarchy process (AHP) and the entropy weight method were combined to determine the weight of each evaluation factor. Pollution loading was evaluated by quantifying the characteristics of potential pollution sources, mainly including pollutant toxicity, pollutant release possibility and potential pollutant release amount. Finally, total iron, Cl^-, SO₄^2-, F^-, COD (Chemical Oxygen Demand), NO₃^-, NO₂^- and TDS (Total Dissolved Solids) are used to calculate the water quality index and verify the model results. The results showed that industries were the most harmful potential pollution sources in the study area, followed by landfills. Very high vulnerability areas were mainly situated around Huazhou District, Huayin and Dali County, as well as the low terraces around Zhouzhi County and Hu County, which are mainly caused by shallow groundwater depth and high net recharge. The final groundwater contamination risk results showed the high groundwater contamination risks are detected around Xi'an City, Xianyang City, Hancheng City and Dali County. Both high vulnerability and high pollution loading were present at the Jingwei District in the north of Xi'an City, where a priority attention should be given.

Assessment of the groundwater quality, physicochemical composition, and human and ecological health risks in a coastal metropolitan: A case study of a residential estate in Lagos, Nigeria

Water is essential for humankind's existence, providing food security, amongst others, as well as promoting industrial and economic development. The physicochemical composition, potentially toxic metals, water quality index, human health, and ecological risks of groundwater in a residential estate in Lagos, Nigeria, were studied to assess their possibility for drinking and domestic purposes. Groundwater samples were collected from twelve designated sites and analysed using standard methods. TDS and pH values of 5.4 ± 1.7-20.8 ± 0.84 and 5.08 ± 0.26-5.56 ± 0.57, respectively, were recorded for the groundwater samples whereas DO and BOD were detected at 4.2 ± 1.2-5.45 ± 0.52 mg O₂/L and 2.6 ± 1.2-24.6 ± 5.7 mg/L, respectively. Additionally, water conductivity ranged from zero to 0.60 ± 0.89 µS/cm. Of the seven PTMs (Pb, Cd, Zn, Cu, Cr, Ni, & Fe) analysed, Pb was present, over the standard limit, in all the samples whereas Fe was detected below the limit in over 83.3% of the groundwater sampled. The hazard index (HI) indicated that 83.3% and 100% of the samples were within the acceptable limits, with no health risks, for the children and adult groups, respectively. WQI showed that 75.0% of the samples was of good quality and suitable for domestic purposes, with low ecological and carcinogenic health risks. The results show that the groundwater samples are good for domestic purposes but require pre-treatment to make them safe for drinking.

Hydrochemical characteristics and groundwater quality in the thick loess deposits of China

Water quality and quantity should be paid more attention in regions with arid climate and thick vadose zones since the limited groundwater cannot be replenished rapidly once polluted. This study focused on the Loess Plateau of China to investigate the geochemical mechanism affecting groundwater chemistry and to calculate contribution rates of multiple sources to groundwater solutes. We employed multiple methods (diagrams, bivariate analyses, hierarchical cluster analysis (HCA), sodium adsorption ratio (SAR), water quality index (WQI), correlation analysis, and forward model) for the above purposes. We collected 64 groundwater samples in the thick loess deposits in June 2018 (flood season) and April 2019 (dry season). The average concentrations of cation were in the order of Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ in the flood season, and Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ in the dry season. The order of anions contents in the flood season and the dry season were HCO₃^- > SO₄^2- > Cl^- > NO₃^-. The major hydrochemical facies were Ca-HCO₃ and Ca·Mg-HCO₃ in the flood season and Na·Ca-HCO₃·SO₄ and Na-HCO₃ in the dry season, respectively. Most of the groundwater (95% in the flood season and 96% in the dry season) was suitable for drinking, and the overall water quality was acceptable for irrigation. Mineral dissolution and cation exchange were important natural processes affecting groundwater chemistry. The forward model showed that the contribution of atmospheric input, anthropogenic input, evaporite dissolution, silicate weathering, and carbonate weathering to solutes in groundwater was 2.3±1.5%, 5.0±7.1%, 19.3±21.4%, 42.8±27.3%, and 30.6±27.1% in the flood season, and 9.1±6.4%, 3.4±5.2%, 20.3±15.9, 56.6±23.2%, and 10.7±15.4% in the dry season, respectively. Obviously, silicate and carbonate weathering contribute the most to groundwater chemistry in the flood season, while silicate weathering and evaporite dissolution contribute the most in the dry season. Although the overall contribution of anthropogenic inputs was insignificant, it was the dominant source of solutes for local groundwater. This study provides fundamental information for water management in arid areas.

Exposure Risk of Global Surface O3 During the Boreal Spring Season

Surface ozone (O₃) is an oxidizing gaseous pollutant; long-term exposure to high O₃ concentrations adversely affects human health. Based on daily surface O₃ concentration data, the spatiotemporal characteristics of O₃ concentration, exposure risks, and driving meteorological factors in 347 cities and 10 major countries (China, Japan, India, South Korea, the United States, Poland, Spain, Germany, France, and the United Kingdom) worldwide were analyzed using the MAKESENS model, Moran' I analysis, and Generalized additive model (GAM). The results indicated that: in the boreal spring season from 2015 to 2020, the global O₃ concentration exhibited an increasing trend at a rate of 0.6 μg/m³/year because of the volatile organic compounds (VOCs) and NOx changes caused by human activities. Due to the lockdown policies after the outbreak of COVID-19, the average O₃ concentration worldwide showed an inverted U-shaped growth during the study period, increasing from 21.9 μg/m³ in 2015 to 27.3 μg/m³ in 2019, and finally decreasing to 25.9 μg/m³ in 2020. According to exposure analytical methods, approximately 6.32% of the population (31.73 million people) in the major countries analyzed reside in rapidly increasing O₃ concentrations. 6.53% of the population (32.75 million people) in the major countries were exposed to a low O₃ concentration growth environment. Thus, the continuous increase of O₃ concentration worldwide is an important factor leading to increasing threats to human health. Further we found that mean wind speed, maximum temperature, and relative humidity are the main factors that determine the change of O₃ concentration. Our research results are of great significance to the continued implementation of strict air quality policies and prevention of population hazards. However, due to data limitations, this research can only provide general trends in O₃ and human health, and more detailed research will be carried out in the follow-up.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12403-022-00463-7.

Assessment of Land Use Land Cover Changes and Future Predictions Using CA-ANN Simulation for Selangor, Malaysia

Land use land cover (LULC) has altered dramatically because of anthropogenic activities, particularly in places where climate change and population growth are severe. The geographic information system (GIS) and remote sensing are widely used techniques for monitoring LULC changes. This study aimed to assess the LULC changes and predict future trends in Selangor, Malaysia. The satellite images from 1991–2021 were classified to develop LULC maps using support vector machine (SVM) classification in ArcGIS. The image classification was based on six different LULC classes, i.e., (i) water, (ii) developed, (iii) barren, (iv) forest, (v) agriculture, and (vi) wetlands. The resulting LULC maps illustrated the area changes from 1991 to 2021 in different classes, where developed, barren, and water lands increased by 15.54%, 1.95%, and 0.53%, respectively. However, agricultural, forest, and wetlands decreased by 3.07%, 14.01%, and 0.94%, respectively. The cellular automata-artificial neural network (CA-ANN) technique was used to predict the LULC changes from 2031–2051. The percentage of correctness for the simulation was 82.43%, and overall kappa value was 0.72. The prediction maps from 2031–2051 illustrated decreasing trends in (i) agricultural by 3.73%, (ii) forest by 1.09%, (iii) barren by 0.21%, (iv) wetlands by 0.06%, and (v) water by 0.04% and increasing trends in (vi) developed by 5.12%. The outcomes of this study provide crucial knowledge that may help in developing future sustainable planning and management, as well as assist authorities in making informed decisions to improve environmental and ecological conditions.

Hydrogeochemistry, identification of hydrogeochemical evolution mechanisms, and assessment of groundwater quality in the southwestern Ordos Basin, China

Understanding the evolution process of hydrogeochemistry and groundwater quality is essential for water supply and health in the southwestern Ordos Basin, where groundwater is a vital source for drinking. This study systematically illustrates the hydrogeochemical characteristics and evolution mechanism based on the groundwater samples (n = 67) collected from Loess area by integrating multivariate statistical methods and hydrogeochemical methods. Furthermore, the entropy water quality index (EWQI) and water quality indices combined with spatial analysis were employed to evaluate the suitability of groundwater for drinking and irrigation purposes and analyze the spatial variation of water quality. The hierarchical cluster analysis and principal component analysis classified groundwater dataset into four clusters and four components which were examined using a Piper diagram and Gibbs diagram, representing different hydrogeochemical characteristics and controlling factors. Based on results, the groundwater chemistry was characterized by representative water types: freshwater (cluster 1, cluster 2), low salinity (half of cluster 3), high salinity (half of cluster 3, cluster 4), and the main controlling factors of hydrogeochemistry revealed by Gibbs diagram were evaporation crystallization (cluster 3, cluster 4) and water-rock interactions (cluster 1, cluster 2). Moreover, the Gaillardet diagram, chloro-alkaline indices, binary diagram, and saturation index further comprehensively illustrate that the silicate and evaporite weathering, ion exchange, dissolution of halite, gypsum, and anhydrite are responsible for hydrogeochemical process. Based on EWQI and ArcGIS, the groundwater quality is categorized as excellent (47.0%), good (31.8%), medium (4.5%), poor (6.1%), and extremely poor (10.6%) types, and the quality in the south of the study area is better than north. Additionally, the USSL diagram shows that most of samples belong to C3S1 (high-salinity hazard and low-sodium hazard) and C2S1 (medium-salinity hazard and low-sodium hazard), and Wilcox diagram shows that 77.2% of samples are suitable for irrigation.

Molecular Engineering of 2D Nanomaterial Field-Effect Transistor Sensors: Fundamentals and Translation across the Innovation Spectrum

Over the last decade, 2D layered nanomaterials have attracted significant attention across the scientific community due to their rich and exotic properties. Various nanoelectronic devices based on these 2D nanomaterials have been explored and demonstrated, including those for environmental applications. Here, the fundamental attributes of 2D layered nanomaterials for field-effect transistor (FET) sensors and tunneling FET (TFET) sensors, which provide versatile detection of water contaminants such as heavy-metal ions, bacteria, nutrients, and organic pollutants, are discussed. The major challenges and opportunities are also outlined for designing and fabricating 2D nanomaterial FET/TFET sensors with superior performance. Translation of these FET/TFET sensors from fundamental research to applied technology is illustrated through a case study on graphene-based real-time FET water sensors. A second case study centers on large-scale sensor networks for water-quality monitoring to enable intelligent drinking water and river-water systems. Overall, 2D nanomaterial FET sensors have significant potential for enabling a human-centered intelligent water system that can likely be applied to other precarious water supplies around the globe.

Hydrogeochemical assessment of groundwater quality and suitability for irrigation in the coastal part of Cuddalore district, Tamil Nadu, India

A study was undertaken to identify in the irrigational suitability of groundwater in the cuddalore district (coastal part), Tamil Nadu, India. An entire study, 132 shallow and deep groundwater samples was gathered during Pre monsoon period (PRM) year of 2017 and post monsoon (POM) period samples collected year of 2018. Rock water interaction, silicate weathering and domestic waste are dominant sources for the water quality in the study area. The groundwater classification and irrigational suitability of groundwater were performed for both seasons. From the results of Chloro-Alkaline Indices (CAI I), and Chloro-Alkaline Indices (CAI II), during both seasons and classes, the direct ions exchange processes are predominant when compare with reverse ions exchange processes. The r₁ and r₂ results represents that most of the samples found as saline sources as Na⁺ - SO₄^2- facies and performing with Deep Meteoric Percolation (DMP) than shallow meteoric percolation During PRM season, r₁ represents 65 (98%) samples for Na⁺ - SO₄^2- facies and 1 (2%) sample represents Na⁺ - HCO₃^- facies and during POM season, r₁ represents 63 (95%) samples for Na⁺ - SO₄^2- facies and 3 (5%) samples represent Na⁺ - HCO₃^- facies respectively. Irrigation water quality parameters like and satisfied the analysed water's irrigation suitability. However, according to MAR parameters, 5% of water samples were unsuitable for irrigation in PRM based on KR parameters, 41% of samples collected in the PRM season only were unsuitable for irrigation. The Wilcox diagram showed that 35% of water samples are suitable for irrigation. Sodium Adsorption Ratio (SAR), Soluble Sodium Percentage (SSP), Magnesium Adsorption Ratio (MAR), Permeability Index (PI), Potential Salinity (PS), and Total Dissolved Solids (TDS) are indicating the irrigational appropriateness of the groundwater samples, which is more suitable in post monsoon season compare to pre monsoon due to enrichment of Na⁺ by seawater intrusion and other processes. During POM season, the most number of groundwater samples are representing excellent to good categories might be due to an effective rainfall recharge by the monsoonal rain in the study area. The parameters indicated the introduction of geogenic and anthropogenic pollutions. The coastal community's knowledge is crucial to the long conservation of coastal water resources.

Sustainable water resources development and management in large river basins: an introduction

Water resources are important in large basins which are important places for human habitation and industrial and agricultural development. The background of editing this thematic issue was introduced and the general water resources situation and water quality status in four major large river basins in the Asian and African continents were briefly summarized to give readers general pictures of water resources development and management in these basins, and these large river basins are the Yellow River Basin, the Yangtze River Basin, the Indus Basin, and the Nile Basin. The thematic issue papers were classified into four clustered topical categories, and the main points of the papers in this thematic issue were summarized. Finally, the perspectives of future sustainable water resources development and management in large river basins were proposed.

Spatio-temporal analysis of groundwater chemistry, quality and potential human health risks in the Pinggu basin of North China Plain: Evidence from high-resolution monitoring dataset of 2015-2017

Long-term monitoring reveals the spatio-temporal evolution of groundwater chemistry, quality and human health risk, providing detailed and robust evidence for groundwater utilization. The Pinggu basin of North China Plain is significant place reserving drinking groundwater. 184 samples were collected from fifty-eight monitoring wells during 2015-2017. Ratios of major ions and geochemical modelling were carried out to clarify the factors controlling the hydrogeochemical compositions. Groundwater displayed the hydrochemical type of Ca-HCO₃ and its compositions were determined by calcite and dolomite dissolution with cation exchange reaction. NO₃^- contamination was derived from agriculture activities. The entropy-weighted water quality index (EWQI) results indicated the majority of total groundwater samples except those in some southwestern and northwestern parts were able to meet the requirement of drinking purposes. Groundwater quality was affected by the total dissolved solid, Ca²⁺, HCO₃^- and NO₃^- concentrations. Human health risk of groundwater drinking depended on the NO₃^- concentration and followed the order of children > adult females ≈ adult males, according to the hazard quotient (HQ) used in the human health risk assessment (HHRA) model. Protection and management measures for groundwater resources were made for the Pinggu basin and other similar areas, based on the spatio-temporal analysis of groundwater chemistry, quality and potential human health risks.

Groundwater Pollution Source Identification and Apportionment Using PMF and PCA-APCS-MLR Receptor Models in Tongchuan City, China

Potential sources of groundwater pollution in Tongchuan City, China, were qualitatively identified based on 14 key water quality indicators of 59 groundwater samples, and the contribution of each source to groundwater quality was quantitatively evaluated. Groundwater pollution sources were analyzed using PMF and PCA-APCS-MLR models, and their applicability in groundwater pollution assessment in Tongchuan City was tested. Results indicate that both models identified four sources of groundwater contamination. Natural evolution was the main cause of groundwater pollution in the study area, followed by the coal industry, agriculture, and urbanization. Although the spatial distribution of pollution sources in the two models differed, the urbanized area to the east of the study area was more severely affected by sewage discharge, the west was more obviously affected by the coal industry, and the north was mainly polluted by agriculture. Both of the fitting results of the two models are good, but R² values obtained by the PMF model (0.4440-0.9991) were generally higher than those obtained by the PCA-APCS-MLR model (0.5180-0.9530), indicating that PMF model results were more accurate than the PCA-APCS-MLR model.

Hydrogeochemical Processes Governing Uranium Mobility: Inferences from the Anthropogenically Disturbed, Semi-arid Region of India

Khetri Copper Belt, Rajasthan, is anthropogenically active and geologically belongs to the Delhi super-group. A study was designed to understand the geochemical processes controlling the elemental mobility in the groundwater. Sampling sites were divided into three zones, i.e. copper, quartzite and granite mine zones depending on the type of mineral excavated. A total of 32 representative groundwater samples were collected and analysed for heavy metals and radionuclide (U) using ICP-MS. A maximum U concentration (average 87 µgL^-1) is observed in the quartzite mine zone, and minimum (average 13 µgL^-1) is found in the copper mine zone samples. A high concentration of U (maximum of 430 µgL^-1) in groundwater is attributed to mineral dissolution due to geogenic and anthropogenic activities. Despite the presence of Jaspura and Gothra granitoid in the copper mine zone, the abundance of U is low suggesting the scavenging of U by sulphides or iron oxides. Additionally, at the confluence of two geological groups, Fe concentration is found high with a low concentration of U which further confirms scavenging of U. It is evident from the results that in the absence of iron-bearing sulphides, U concentration in groundwater would be very high compared to the current concentration. It also indicates low concentration of U in the copper mine zone is due to dissolution of Fe sulphide-rich waste. The present study recommends further research to understand the feasibility of mining waste for the removal of U contamination from groundwater.

Evaluation of Health Risk after Nitrate Exposure in Drinking Water in the Al Duliel Area, Jordan

&lt;b&gt;Background and Objective:&lt;/b&gt; Jordan's drinking water scarcity is desperately needed and it plays a critical role in improving safe drinking water quality, which is critical for nutritious and clean drinking water quality, which is a vital component of good public health. Recognize the potential risk of repeated exposure to high nitrate concentrations in drinking water in the A Duliel area and measure the impact on local communities' human health. &lt;b&gt;Materials and Methods:&lt;/b&gt; In 2016, samples of groundwater were taken. With a mean value of 44.4 mg L&lt;sup&gt;1&lt;/sup&gt;, nitrate concentrations ranged from 10-81.0 mg L&lt;sup&gt;1&lt;/sup&gt;. &lt;b&gt;Results:&lt;/b&gt; The findings showed that human activities, especially the extensive use of chemical fertilizers in agriculture, could be attributed to high NO&lt;sub&gt;3&lt;/sub&gt; concentrations. To assess the possible risk to human health, Chronic Daily Intake (CDI) and Hazard Quotient (HQ) has been assessed. In the classes considered, infants tended to be at a greater risk than children and adults. Furthermore, the findings showed that in most of the groundwater considered, the health of people from nitrate contamination was not adequate and was also at risk from known concentrations of nitrate. &lt;b&gt;Conclusion:&lt;/b&gt; Appropriate steps to improve groundwater protection and to better track and control stable sources of nitrate emissions are also important.

Assessment of groundwater quality and usability of Salda Lake Basin (Burdur/Turkey) and health risk related to arsenic pollution

PURPOSE

In this study the aim was to analyze the seasonal concentration, groundwater quality, usage areas and arsenic-related health risk of major ions and heavy metals in groundwater samples collected from the Salda Lake basin.

METHODS

In this study, 42 groundwater samples were collected from springs and wells in dry and wet seasons in 2015. Hydrogeochemical evaluations were made using different diagrams such as Piper and Gibbs diagrams. Groundwater quality was determined by the water quality index method (WQI) and different diagrams. Finally, health risk assessments related to arsenic were performed.

RESULTS

The dominant water types are Mg-Ca-HCO3 and Mg-HCO3 in the wet season and Mg-HCO3 and Mg-HCO3-CO3 in the dry season. According to calculated WQI values ranged from 24.14 to 56.93 in the wet season ranged from 25.27 to 145.87 in dry season. This situation indicates that the quality of water samples is mostly good both seasons. AsT concentrations were between 2.1-6.3 μg/L in the dry season and 2.9-10.5 μg/L in the wet season. The risk of developing cancer due to arsenic exposure in healthy adults or children is very low. But arsenic has high non-carcinogenic and carcinogenic potentially harmful effect in the study area. In addition, water samples are not appropriate for use as drinking water in terms of fertilizers and trace element concentrations. Also, MH will be an important problem in waters that will be used as irrigation water. The use of some samples is not recommended as it may cause crusting on metal surfaces in industrial areas.

CONCLUSIONS

According to the results obtained, the quality of groundwater in the study area should be monitored and the usage areas should be determined accordingly.

Fluoride contamination in and around selected geothermal sites in Odisha, Eastern India: assessment of ionic relations, fluoride exposure and remediation

Fluoride contamination in groundwater is a major problem throughout the world as well as in India. High-fluoride content was reported in the hot springs of Atri and Tarbalo sites in Odisha, India, and residents of nearby villages showed the manifestations of fluorosis. Around 39% of the groundwater samples showed fluoride concentration > 1 mg/l, higher than the desirable limit specified by the WHO. The dominant chemical facies of groundwaters were ions of Ca-Mg-HCO₃ and Ca-Na-Cl, which infers the lithological control over the hydrochemistry of this area. A strong correlation between fluoride and other major ions could not be found, suggesting that multiple processes are responsible for the enriched fluoride concentration observed in the study area. The major geochemical processes include dissolution of fluoride-bearing minerals from the rocks, evapotranspiration, agricultural input and mixing of cold groundwater with hot spring water containing high fluoride. The maximum fluoride exposure doses through drinking water from fluoride-contaminated tube wells were estimated to be 0.07 mg/kg/d for infants, 0.125 mg/kg/d for children and 0.06 mg/kg/d for adults, which are higher than the minimum risk level (0.05 mg/kg/d). Exposure doses of fluoride indicate that exposure risk is doubled for children in comparison to infants and adults, which might cause severe dental fluorosis and other ailments. Considering the environmental and hydrological set up of the study area, membrane defluoridation process can be suggested as the best remediation method. Nalgonda technique, dilution of fluoride-rich groundwater and better nutrition containing calcium and vitamin C are other possible options that can be included for early mitigation of fluoride contamination.

Linkage analysis of water resources, wastewater pollution, and health for regional sustainable development-using undesirable three-stage dynamic data envelopment analysis

With the development of China's economy, pollution has made serious impact on environment and human health. However, environmental protection and residents' health are becoming more and more important along with the country's social and economic transformation. Most existing studies have analyzed the path of economic impact on the environment and the production, pollution, and health in isolation. This research takes panel data of 30 provinces in China (including autonomous regions and municipalities, excluding Tibet, Hong Kong, Macau, and Taiwan) spanning 2014 to 2017 as an example, builds an evaluation indicator system on the basis of the three stages of economic production, wastewater treatment, and human health, and uses the undesirable three-stage dynamic data envelopment analysis model to empirically evaluate the total efficiency, stage efficiency, and the efficiency of various indicators. The research results show the average efficiency of the three stages in most provinces in four years is below 0.5, indicating the poor coordination of each stage; the efficiency gaps among the eastern, central, and western regions are very large because of the resource endowments, geographical environment, industrial structure, strategic adjustment, and other infactors. The total efficiency of the three stages of production input, wastewater treatment, and health output in the eastern region are higher than that of the central region and the western region. From the perspective of stage efficiency, most of the 30 provinces exhibit production efficiency < health efficiency < wastewater treatment efficiency. For the three-phase input and output indicators, the efficiency values and development trends of different provinces vary. The efficiencies of input variables in the wastewater treatment stage and health stage are low in most provinces. This means that the provinces should implement accurate policies according to their own evaluation results and improve the relevance and coordination among the three stages through reasonable allocation of medical input and arrangement of urban employment.

Applications of geochemical and multivariate statistical approaches for the evaluation of groundwater quality and human health risks in a semi-arid region of eastern Maharashtra, India

A qualitative approach, including geochemical and multivariate statistical approaches, is applied to evaluate the groundwater quality and human health risk, based on analytical data of 72 samples collected from a semi-arid region of eastern Maharashtra, India. The shifting of hydrochemical type from Ca²⁺-Na⁺-[Formula: see text] to Na⁺-Ca²⁺-Cl^- type was observed along different flow paths. The main controlling processes observed from the chemical characterisation of the groundwater are water-rock interactions, dedolomitisation and reverse ion exchange. Simulation analysis (mass transfer) exposes the dissolution of dolomite, gypsum, halite, k-feldspar and CO₂ down the simulated pathways. Around 77% of the total variance was observed from the first three principal component analyses. The high positive loadings of EC, TDS, Na⁺, K⁺, Ca²⁺, Cl^-, [Formula: see text] and [Formula: see text] of PC1 revealed silicate weathering and reverse ion exchange followed by human activities as the contamination sources. The sources identified for high positive loadings on [Formula: see text] and [Formula: see text] of PC2 are soil CO₂ and human activities. The high loadings of pH and F^- in PC3 revealed fluorite dissolution and calcite precipitation. The human health risk calculated for [Formula: see text] revealed that 58% and 44% of the total groundwater samples surpassed the tolerance limit for non-carcinogenic risk of 1.0 in children and adults. The human health risk assessment for fluoride showed high hazard index values in 40% and 23% of the total groundwater samples for children and adults, respectively. The study suggests some management measures for protection of groundwater resources.

Poor groundwater quality and high potential health risks in the Datong Basin, northern China: research from published data

Datong Basin in China is a typical arid-semiarid inland basin, with high levels and wide distributions of arsenic (As), fluoride (F^-), and iodine (I). To better understand the presence of low-quality groundwater in Datong Basin and assess the health risks for local residents, groundwater samples were collected from the shallow aquifer and in medium-deep groundwater and analyzed for As, F^-, I, and nitrate (NO₃^-). Maxima of 1932 μg/L for As, 80.89 mg/L for F^-, 2300 μg/L for I, and 3854.74 mg/L for NO₃^- were detected in shallow groundwater, which greatly exceeded the WHO limits for drinking purpose. High-As groundwater was present in both shallow and medium-deep aquifers. High-F^- and high-NO₃^- groundwater was widely distributed in the shallow aquifer, and high-I groundwater was mainly present in the medium-deep aquifers. Poor-quality groundwater in the Datong Basin is mainly caused by local geological and climatic conditions, which are characterized by strong evaporation, active water-rock interactions, thick lacustrine sediment, low groundwater flow rate, and reducing and weak alkaline environments. However, groundwater quality was further impacted by agricultural activities in some areas, as shallow groundwater was also polluted by nitrate. Datong Basin inhabitants face high health risk caused by high concentrations of As, F^-, I, and NO₃^-. The mean noncarcinogenic risk values (HQ_total) were 18.40 for children, 10.94 for adult females, and 9.47 for adult males due to exposure to contaminants in shallow groundwater; and 13.76 for children, 8.18 for adult females, and 7.08 for adult males because of exposure to medium-deep groundwater. Further, the carcinogenic risks (CR) caused by exposure to As were very high for local inhabitants, with the mean and median CR values of 4.20×10^-3 and 4.13×10^-4 in shallow groundwater and 3.44×10^-3 and 1.71×10^-4 in medium-deep groundwater, respectively.