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

Coordinated analysis of groundwater spatiotemporal chemical characteristics, water quality, and potential human health risks with sustainable development in semi-arid regions

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl-Ca·Mg and HCO3-Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3-, TH, TDS, and SO42-. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.

Spatial health risk assessments of nickel in the groundwater sources of a mining-impacted area

Mining activities have increased the potential risks of metal pollution to the groundwater resources in arid areas across the globe. Therefore, this study aimed to examine the health risk associated with nickel (Ni) in the groundwater sources of a mining-impacted area, South Khorasan, Eastern Iran. A total of 110 stations were included in the study, comprising 62 wells, 40 qanats, and 8 springs in summer, 2020. Initially, the collected samples were tested for temperature, pH, and electrical conductivity (EC). Subsequently, the samples were filtered and treated with nitric acid (HNO3) to measure the concentration of Ni using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Hazard quotient (HQ) and non-carcinogenic risk assessments were employed to evaluate the potential risks of Ni to the inhabitants. The findings revealed that the concentration of Ni ranged from 0.02 to 132.39 μg l-1, and only two stations exhibited Ni concentrations above the WHO standards (20 μg l-1). The results demonstrated that 98.21% of the sampled locations had HQ values below one, indicating negligible risk, while 1.78% of the stations exhibited HQ values of one or higher, representing a high non-carcinogenic risk for water consumers. Overall, the concentration of nickel in the groundwater of South Khorasan exceeded the World Health Organization (WHO) limit solely in the Halvan station, posing a non-carcinogenic risk for the residents in that area, and therefore, additional efforts should be made to provide healthier groundwater to consumers in this region.

Evaluation of sustainable development capacity of water sources: a case study of China

The issue of water scarcity has drawn attention from all over the world. The coordination of the interaction between ecological and environmental development of water sources and socio-economic development is currently an essential issue that needs to be solved in order to safeguard the water resources environment for human survival. In this essay, we suggest a paradigm for assessing the sustainable exploitation of water resources. First, three ecological, economic, and social factors are investigated. Twenty essential evaluation indexes are then constructed using the Delphi approach, along with an index system for assessing the potential of water sources for sustainable development. The weights of each evaluation index were then determined using the combination assignment approach, which was then suggested. The coupled degree evaluation model of the capability for sustainable development of water sources was then developed. In order to confirm the viability and validity of the suggested model, the model was used to assess the Liwu River water source's capacity for sustainable growth in the context of the South-North Water Transfer in Shandong, China. It is believed that the aforementioned study would serve as a helpful resource when evaluating the capacity of water sources for sustainable development.

Hydro-chemical based assessment of groundwater vulnerability in the Holocene multi-aquifers of Ganges delta

Determining the degree of high groundwater arsenic (As) and fluoride (F-) risk is crucial for successful groundwater management and protection of public health, as elevated contamination in groundwater poses a risk to the environment and human health. It is a fact that several non-point sources of pollutants contaminate the groundwater of the multi-aquifers of the Ganges delta. This study used logistic regression (LR), random forest (RF) and artificial neural network (ANN) machine learning algorithm to evaluate groundwater vulnerability in the Holocene multi-layered aquifers of Ganges delta, which is part of the Indo-Bangladesh region. Fifteen hydro-chemical data were used for modelling purposes and sophisticated statistical tests were carried out to check the dataset regarding their dependent relationships. ANN performed best with an AUC of 0.902 in the validation dataset and prepared a groundwater vulnerability map accordingly. The spatial distribution of the vulnerability map indicates that eastern and some isolated south-eastern and central middle portions are very vulnerable in terms of As and F- concentration. The overall prediction demonstrates that 29% of the areal coverage of the Ganges delta is very vulnerable to As and F- contents. Finally, this study discusses major contamination categories, rising security issues, and problems related to groundwater quality globally. Henceforth, groundwater quality monitoring must be significantly improved to successfully detect and reduce hazards to groundwater from past, present, and future contamination.

Groundwater nitrate pollution risk assessment based on the potential impact of land use, nitrogen balance, and vulnerability

The predicting groundwater nitrate pollution risk, especially in terms of changes in fertilizing, has not been fully investigated so far. In particular, there is no comprehensive method to assess this risk in areas of different land use type, and not only in agricultural areas. The aim of this study was to develop a novel multicriteria methodology for groundwater nitrate pollution risk assessment, which meets these issues. A further aim was to determine how much this risk would change if the amount of organic and synthetic fertilization was reduced. An assumption was that groundwater pollution risk is a combination of the potential adverse impacts of land use, fertilization, and intrinsic groundwater vulnerability to pollution. The impact of fertilization was holistically evaluated by balancing nitrogen from spatially differentiated the size of the breeding, species of livestock, manure and synthetic fertilizers input, and spatially differentiated topsoil, with nitrogen uptake by different crops. The nitrate concentration in the leachate was used as a measure of the impact of fertilization. This concentration was compared to the natural baseline nitrate concentration in groundwater. Three fertilization scenarios for groundwater pollution risk assessment in two study areas were discussed. Under typical agricultural, climatic, soil, and geological conditions in Europe for the current total fertilization level of 95-120 kg N ha-1 groundwater nitrate pollution risk is low and moderate, but for fertilization of 150-180 kg N ha-1, a reduction in the total fertilization (synthetic and manure) by 40 to 50% may be required to achieve low risk of degradation of natural groundwater quality. Predictive simulations of groundwater nitrate pollution risk confirmed that reducing synthetic and organic fertilization has an effect, especially in areas with intensive fertilization. This method may allow for a holistic and scenario-based assessment of groundwater pollution risk and may help decision-makers introduce solutions to manage this risk under conditions of climate change, preservation of groundwater quality, and food security.

Hydrogeochemical evaluation with emphasis on nitrate and fluoride in urban and rural drinking water resources in western Isfahan province, central Iran

Nitrate (NO3-) and fluoride (F-) are two major potential contaminants found in the groundwater of Iran. These contaminants are highly dangerous to humans if consumed more than the safe limit prescribed by the WHO. Therefore, in this study, the urban and rural drinking water resources of Isfahan province (central Iran) were investigated to evaluate the quality of groundwater from the perspective of NO3- and F-. The calculated saturation index (SI) shows that the majority of samples are mainly undersaturated or in equilibrium with respect to potential minerals. The most likely interpretation for undersaturation with respect to most minerals is either that the minerals are not present if they are reactive or if they are present, then they are not reactive. This study reveals that the majority of the groundwater samples belong to the Ca-Mg-HCO3 water type. Further, in this study, potential physicochemical variables have been used to calculate entropy weighted water quality index (EWQI). The EWQI reveals that the majority of the groundwater in the area is of good quality. Results show that the water chemistry in the area is largely governed by the water-rock interaction. This study based on large data sets reveals that the majority of drinking water resources are uncontaminated by F-. However, the groundwater is found to be largely contaminated by NO3-. The bivariate plot suggests that the unscientific farming practices and overuse of manures and fertilizers are largely responsible for high content of NO3-. Therefore, emphasis should be given on the cost-effective environmentally friendly fertilizers. The findings from this study will aid the governing authorities and concerned stakeholders to understand the hydrogeochemical evolution of groundwater in this region. The results will help formulate policies in the area for sustainable water supply.

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.

Combining multi-isotope technology, hydrochemical information, and MixSIAR model to identify and quantify nitrate sources of groundwater and surface water in a multi-land use region

Accurate identification of nitrate (NO3-) sources is the premise of non-point source pollution control in watersheds. The multiple isotope techniques (δ15N-NO3-, δ18O-NO3-, δ2H-H2O, δ18O-H2O), combined with hydrochemistry characteristics, land use information, and Bayesian stable isotope mixing model (MixSIAR), were used to identify the sources and contributions of NO3- in the agricultural watershed of the upper Zihe River, China. A total of 43 groundwater (GW) and 7 surface water (SFW) samples were collected. The results showed that NO3- concentrations of 30.23% GW samples exceeded the WHO maximum permissible limit level, whereas SFW samples did not exceed the standard. The NO3- content of GW varied significantly among different land uses. The averaged GW NO3- content in livestock farms (LF) was the highest, followed by vegetable plots (VP), kiwifruit orchards (KF), croplands (CL), and woodlands (WL). Nitrification was the main transformation process of nitrogen, while denitrification was not significant. Hydrochemical analysis results combined with NO isotopes biplot showed that manure and sewage (M&S), NH4+ fertilizers (NHF), and soil organic nitrogen (SON) were the mixed sources of NO3-. The MixSIAR model summarized that M&S was the main NO3- contributor for the entire watershed, SFW, and GW. For contribution rates of sources in GW of different land use patterns, the main contributor in KF was M&S (contributing 59.00% on average), while M&S (46.70%) and SON (33.50%) contributed significantly to NO3- in CL. Combined with the traceability results and the situation that land use patterns are changing from CL to KF in this area, improving fertilization patterns and increasing manure use efficiency are necessary to reduce NO3- input. These research results will serve as a theoretical foundation for controlling NO3- pollution in the watershed and adjusting agricultural planting structures.

Assessment of groundwater vulnerability by applying the improved DRASTIC model: a case in Guyuan City, Ningxia, China

Groundwater is the main source of production and living in most arid and semi-arid areas, and it plays an increasingly critical role in achieving local urban development. There is a serious issue regarding the contradiction between urban development and groundwater protection. In this study, we used three different models to assess the groundwater vulnerability of Guyuan City, including DRASTIC model, analytical hierarchy process-DRASTIC model (AHP-DRASTIC) and variable weight theory-DRASTIC model (VW-DRASTIC). The groundwater vulnerability index (GVI) of the study area was calculated in ArcGIS. Based on the magnitude of GVI, the groundwater vulnerability was classified into five classes: very high, high, medium, low, and very low using the natural breakpoint method, and the groundwater vulnerability map (GVM) of the study area was drawn. In order to validate the accuracy of groundwater vulnerability, the Spearman correlation coefficient was used, and the results showed that the VW-DRASTIC model performed best among the three models (ρ=0.83). The improved VW-DRASTIC model shows that the variable weight model effectively improves the accuracy of the DRASTIC model, which is more suitable for the study area. Finally, based on the results of GVM combined with the distribution of F^- and urban development planning, suggestions were proposed for further sustainable groundwater management. This study provides a scientific basis for groundwater management in Guyuan City, which can be an example for similar areas, particularly in arid and semi-arid areas.

Comparative assessment of groundwater vulnerability using GIS-based DRASTIC and DRASTIC-AHP for Thoothukudi District, Tamil Nadu India

The groundwater is very precious in the world. Rapid urbanization and industrialization create tremendous stress on groundwater quality and quantity. Unscientific groundwater extraction and waste disposal methods impact the groundwater aquifer's susceptibility in the coastal area. This research examines how industrial waste, seawater intrusion, and solid waste dumping affect the Thoothukudi District, located on the southwest coast of Tamil Nadu, India. The groundwater vulnerability potential is determined using the DRASTIC and analytical hierarchy process (AHP)-based DRASTIC model. DRASTIC-AHP method's weights and ranks are determined using multi-criteria decision analysis (MCDA)-based pairwise comparison method. Remote sensing (RS) and geographical information system (GIS) are implemented to prepare the input layers for DRASTIC and DRASTIC-AHP. The findings reveal a very high category of vulnerability along the coastline that is covered in sand and loose sediments from an aquifer. Similar conditions exist on the southeast side, which is covered with gravel, sand, and sandstone with shale and has relatively low-slope topography. This enables higher contaminant percolation into the groundwater and raises the possibility for pollution. The DRASTIC-AHP method's results reveal that the southeast side has a significant possibility of contamination. The water table, net recharge, vadose zone, and conductivity greatly impacted the DRASTIC vulnerability assessment due to their stronger weight than theoretical weight. It may be stated that the DRASTIC technique is more cost-effective and time-efficient in analyzing a wide range of regional groundwater risks while avoiding sloppy, uncontrolled land development and other unwanted activities.

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.

A framework model to determine groundwater contamination risk based on a L-Matrix of aquifer vulnerability and hazardous activity indices

The method presented in this study assesses groundwater contamination risk using a L-Matrix system approach. The L-Matrix in this case is a cartesian diagram where the XX-axis represents aquifer vulnerability (0≤V≤1) determined by the well-known DRASTIC model, and the YY-axis represents the potential hazardousness (0≤H≤1) of an activity (infrastructural development, industrial activities, livestock and agriculture) measured by a European Commission approach. The diagram is divided into four regions, the boundaries of which are set to V = 0.5 and H = 0.5. Watersheds are represented in this diagram considering their V and H indices, and assigned a potential contamination risk if groundwater sites located within their limits show contaminant concentrations above legal limits for a given use. Depending on the region the watershed falls in the L-Matrix diagram, different management or contamination prevention actions are highlighted: activity development, activity monitoring, activity planning or activity inspecting. Watersheds located in the inspecting region and simultaneously evidencing contamination risk require immediate action, namely conditioning or even suspension of use. The method is tested in the Paraopeba River basin (Minas Gerais, Brazil), a densely industrialized basin that was recently affected by an iron-ore mine tailings dam break.•

The L-Matrix diagram highlights different groundwater susceptibility realities experienced by watersheds with different combinations of aquifer vulnerability and activity hazardousness, namely possibility for potential expansion of new hazardous activities but also the necessity to periodically inspect and eventually condition or suspend others.

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The L-Matrix diagram is likely a better approach to implement contamination prevention measures in watersheds, than the integrated contamination risk index used by most methods.

Characteristics of Hydro-Geochemistry and Groundwater Pollution in Songnen Plain in Northeastern China

Agricultural production may cause groundwater pollution. This study investigated the characteristics of shallow groundwater pollution in a typical black land agricultural production area in Northeastern China and the geochemical behavior of major pollutants. A total of 27 and 23 shallow groundwater samples were collected for measuring on-site parameters and major components in 2000 and 2014, respectively. The improved integrated approach was used to assess groundwater contamination. The results showed that the groundwater was slightly polluted by agricultural activities. The average concentrations of major ions of shallow groundwater were found to be in the following order: Ca2+ > Na+ > Mg2+ > K+ for cations and HCO3− > SO42− > Cl− > NO3− for anions. Percentages of 7.4% and 34.8% of the total groundwater sample in 2000 and 2014, respectively, indicated that the shallow groundwater quality has gradually worsened in the past few decades. The concentration of NO3− was a major factor that influenced the observed groundwater quality changes. Scientific and effective fertilization of rice cultivation is an effective way to avoid groundwater pollution, and the improved groundwater quality evaluation methods can further improve the standard of groundwater resource management effectively.

Hydrochemical Characteristics of Arsenic in Shallow Groundwater in Various Unconsolided Sediment Aquifers: A Case Study in Hetao Basin in Inner Mongolia, China

This study focused on the entire Hetao Basin, which can fall into four hydrogeological units, the Houtao Plain, Sanhuhe Plain, Hubao Plain, and South Bank Plain of the Yellow River, all of which are under different geological and environmental conditions. To systematically investigate the hydrochemical characteristics and spatial distribution of high-As groundwater (As > 10 μg/L), 974 samples were collected from shallow groundwater. As indicated from the results, high-As groundwater had an extensive distribution, and its spatial distribution in the four hydrogeological units exhibited significant variability. Three concentrated distribution areas were reported with high-As groundwater, which were all in the discharge areas of groundwater, and the arsenic contents in the groundwater were found to exceed 50 μg/L. The hydrochemical types of high-As groundwater in the HT Plain and the SHH Plain consisted of HCO3 SO4·Cl for anions and Na for cations, while those in the other two plains included HCO3 for anions as well as Na·Mg·Ca for cations. According to the pH values, the groundwater was weakly alkaline in the areas with high-As groundwater, and arsenic primarily existed as arsenite. Furthermore, high-As groundwater in the Hetao Basin was characterized by high contents of Fe (mean value of 2.77 mg/L) and HCO3− (mean value of 460 mg/L) and a low relative concentration of SO42− (average value of 310 mg/L). This study did not identify any significant correlation between groundwater arsenic and other ions (e.g., Fe2+, Fe3+, HCO3−, SO42−, NO2− and NO3−) in the entire Hetao Basin over a wide range of hydrogeological units. The results remained unchanged after the four hydrogeological units were analyzed. The special sedimentary environment evolution of the Hetao Basin was found as the prerequisite for the formation of high-arsenic groundwater. Furthermore, groundwater runoff conditions and hydrogeochemical processes in the basin were indicated as the factors controlling the formation of high-arsenic groundwater.

Health Risk of the Shallow Groundwater and Its Suitability for Drinking Purpose in Tongchuan, China

Studying the quality and health risks of groundwater is of great significance for sustainable water resources utilization, especially in arid and semi-arid areas around the world. The current study is carried out to evaluate the quality and potential health risks of groundwater in the Tongchuan area on the Loess Plateau, northwest China. Water quality index (WQI) and hydrochemical correlation analysis were implemented to understand the status of groundwater quality. Daily average exposure dosages through the oral and dermal contact exposure pathways were taken into consideration to calculate the health risks to the human body. Additionally, graphical approaches such as Piper diagram, Durov diagram and GIS mapping were used to help better understand the results of this study. The WQI approach showed that 77.1% of the samples were of excellent quality. The most significant parameters affecting water quality were NO3−, F−, and Cr6+. The health risk assessment results showed that 27.1% and 54.2% of the samples lead to non-carcinogenic risks through oral intake for adults and children, respectively. In contrast, 12.5% of the groundwater samples would result in carcinogenic risks to the residents. This study showed that the WQI method needs to be supplemented by a health risk evaluation to obtain comprehensive results for groundwater quality protection and management in the Tongchuan area.