Groundwater Quality Research Articles

Assessment of groundwater quality for agricultural purposes in Qazvin Province, northwestern Iran: A fuzzy inference and indicator Kriging approach

This study addresses the challenge of assessing groundwater quality for agriculture in Qazvin Province, northwestern Iran. In this region, over-extraction has led to significant degradation of groundwater resources. Traditional assessment methods often overlook uncertainties and spatial variability in groundwater quality. To address this, our study aimed to integrate fuzzy inference and geostatistical methods to assess groundwater quality under uncertain conditions. The research was conducted in two stages. First, a fuzzy inference system classified six key water quality parameters: Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), Residual Sodium Carbonate (RSC), Total Hardness (TH), sodium ion concentration (Na⁺), and chloride concentration (Cl⁻), into three categories: "desirable," "acceptable," and "unacceptable," using 54 fuzzy rules. In the second stage, we applied ordinary Kriging and indicator Kriging to spatially interpolate these classifications and produce probabilistic maps of groundwater quality risk across the study area. In ordinary Kriging, the average Root Mean Square Error (RMSE) values for EC, SAR, RSC, TH, Na⁺, and Cl⁻ were 0.94 dS/m, 1.54, 1.42 meq/L, 3.13 mg/L, 3.03 mg/L, and 2.62 mg/L, respectively, indicating reliable assessments of groundwater quality parameters. Results also suggest that by 2023, areas classified as "unacceptable" increased by 142.0% since 2009, with an additional 25.2% of the region facing a 40 to 80% probability of further degradation. These findings highlight important trends in groundwater quality, assisting local authorities in prioritizing areas for preventive interventions. This supports sustainable agricultural practices and aligns with the United Nations Sustainable Development Goal 6 for water resource management.

Application of selected indicators to assess contamination of municipal landfill leachate and its impact on groundwater

Leachate formation is one of the most important factors taken into account during the operation and long-term management of municipal waste landfills. Systematic assessment of groundwater and leachate contamination may be useful in selecting the appropriate method of leachate management or treatment processes. The use of indicators to quantify the contamination potential of leachate and groundwater in the vicinity of MSW could help landfill managers assess their quality. Therefore, the aim of the study was to assess the representativeness of selected indicator methods for analyzing the temporal variability of leachate and groundwater properties in the vicinity of two municipal waste landfills in a Central European country (Poland). The leachate pollution index (LPI), sub-LPI and adjusted leachate pollution index (r-LPI) were used to assess the quality of leachate water, while the landfill water pollution index (LWPI) was used to assess the variability of groundwater quality. The results confirmed that LWPI is an effective method for assessing the quality of groundwater in the vicinity of municipal waste landfills. The obtained results confirm the negative impact of landfills, despite the insulation used. LWPI showed poor quality of groundwater and visible impact of the landfill (landfill W, average LWPI - 2.34) and moderately polluted waters and minor impact of the landfill (landfill S, average LWPI - 1.37). In most cases, it was observed that two parameters, EC and TOC, are the main factors contributing to the deterioration of groundwater quality. The sub-LPI analysis showed that leachates from both landfills have a very low content of heavy metals, so they should not have a negative impact on the biological treatment process. The obtained r-LPI values were in all cases higher than the calculated LPI values. For landfill S, the average r-LPI was 26.3 (Z-1) and 25.7 (Z-2). However, the average LPI was 13.5 (Z-1) and 13.2 (Z-2). For landfill W, the average r-LPI was 14.6 and the average LPI was 11.4. Analysis conducted on multi-year leachate and groundwater data using specific indicators can help managers better understand the impact of MSW on surrounding areas and help avoid potential operational problems in the future.

Identifying the pattern of shallow groundwater hydrochemistry and its driving factors in a typical estuarine delta of Poyang Lake watershed, China: Insights into water quality assessment

Study regionA typical estuarine delta of Gan−Xiu River within Poyang Lake watershed, situated in the north of Jiangxi Province, China Study focusAlthough groundwater is considered as a crucial water resource for social development and public health, it presents significant challenges in preventing the deterioration of groundwater quality in the seasonal floodplain regions. Hence, this study focuses on the spatiotemporal variations of ionic concentrations of shallow groundwater in an estuarine delta of Gan-Xiu River in Poyang Lake watershed, which is greatly complicated by complex hydrological regimes and intensive anthropogenic activities such as cropland fertilizer. The potential factors controlling the ionic concentrations were identified using self-organizing map clustering and Piper diagram approaches. Moreover, the overall water quality of shallow groundwater was assessed according to the ionic compositions. New hydrological insights for the region(1) Shallow groundwater chemistry was influenced by weathering silicate and carbonate from ionic and Gibbs plots, which is highly associated with the distribution of the carbonate rock fissure-karst aquifer in the study region. (2) The contribution of groundwater to river water varied from 53.2% to 71.5% via isotopic analysis, suggesting that groundwater dominate the component of river water. (3) Most samples from cluster types are suitable for drinking and irrigation use except for sites from Cluster 6, which were characterized by the higher concentrations of Cl−, NO3− and SO42−.

A common framework for the development of spring water contamination early warning system in western Mediterranean karst areas: Spanish and French sites

Karst water resources, traditionally used worldwide for drinking purposes, are highly vulnerable to contamination. Scientific-technical efforts must therefore be done to ensure sufficient water quality for human consumption. Early-Warning-Systems emerge as an effective spring scale protection strategy for real-time identification of contamination episodes at drinking water capture points. With this ambition, the proposed stepwise procedure for the implementation of site-specific Early-Warning-Systems (EWS), focuses on three critical features: identification of groundwater contamination proxy parameters, warning dissemination and system validation. It was tested at three karst springs affected by temporary faecal contamination and intended for supplying drinking water to populations in Spain (Ubrique) and France (Montpellier). The applied statistical techniques, coupled to the analysis of individual flood events at karst springs, allowed to identify the optimal combination of groundwater and contamination proxy parameters at each study site according to the main contaminants and recharge mechanisms. The decision tree-like workflow, used to evaluate groundwater quality at hourly time step and set up the EWS, was then constructed considering a specific combination of hydroclimatic, hydrodynamic and physical variables together with national regulations for drinking water. Hence, warning thresholds were adapted to the behaviour of each karst system, and used to trigger the alarm when specific parameters and proxies exceeded the defined limits. The performance of the EWS was assessed by implementing 4 specific Key Performance Indicators (KPIs) dedicated to appreciate the effectiveness of the workflows in identifying contamination events and verifying estimated warning thresholds. The performed analysis demonstrated an overall successful functioning of the EWS for the three case studies, with mean anticipation times ranging between 12 and 45 h and <3 % of failure rate.

Effect of inorganic salt composition on strength, microstructure and leaching toxicity of coal-based solid waste backfill materials

This study explores the potential of coal-fired slag, desulfurized gypsum and modified magnesium slag as cementing agents for coal-based solid waste backfill materials. Inorganic salts like CaCl2, Na2SO4 and Na2SiO3 were used as excitants to investigate their combined impact on the mechanical properties, microstructure and leaching risk of hazardous elements from the coal-based solid waste backfill materials. The findings show that the addition of inorganic salt boosts the alkalinity within the liquid-phase reaction system. This disrupted the hydration-blocking membrane, accelerating the dissolution and reaction rate of the silica-alumina mineral components within the cementitious material. Concurrently, the inorganic salt ions consumed the early alkaline hydration products, destroying the hydration reaction equilibrium and facilitating the formation of hydration products like AFt, C-S-H gel, C-A-S-H gel, and Friedel's salt. This increase in the solid-phase volume content and microscopic densities in the reaction system improved the early mechanical properties of the coal-based solid waste backfill materials. Additionally, after a 28-day curing period, the leaching concentration of deleterious elements in the coal-based solid waste backfill material containing inorganic salt components was below the permissible concentration limit of the Class III groundwater quality standard. This eco-friendly backfill material is promising for mine backfilling, a potential substitute for traditional cement-based backfill material.

Environmental Factors Influencing Groundwater Quality and Health Risks in Northern Henan Plain, China

Environmental Factors Influencing Groundwater Quality and Health Risks in Northern Henan Plain, China

Increasing Water Supply Resilience Through the Pure Water Antelope Valley Program

Key TakeawaysThe Pure Water Antelope Valley (AV) program, the first inland potable reuse program in California, aims to augment water supplies to overcome current and projected reductions.Pure Water AV will use groundwater recharge via subsurface injection to increase the reliability and resilience of Antelope Valley's water supply.A collaboration between the Palmdale Water District, City of Palmdale, and Los Angeles County Sanitation Districts, the program will improve the groundwater quality over time.Besides overcoming technical challenges, Pure Water AV's success depends on well‐thought‐out strategies for funding and public outreach.

Hydrochemical assessment of groundwater quality in the coastal belt of Sindh, Pakistan: Implications for human health

Hydrochemical assessment of groundwater quality in the coastal belt of Sindh, Pakistan: Implications for human health

Hydrochemical Assessment of Groundwater Quality in the City of Manga and the Surrounding Area, Burkina Faso, West Africa

Hydrochemical Assessment of Groundwater Quality in the City of Manga and the Surrounding Area, Burkina Faso, West Africa

Monitoring soil salinization and waterlogging in the northeastern Nile Delta linked to shallow saline groundwater and irrigation water quality.

Soil salinization and waterlogging are critical environmental issues affecting agricultural productivity and cultural heritage preservation, particularly in arid regions. This study investigated soil degradation processes in the archaeologically and agriculturally significant northeastern Nile Delta of Egypt. The objective was to assess the severity of soil degradation and identify key drivers related to water resources and soil characteristics to aid in the development of management strategies. The research employed a multi-faceted approach, including hydrochemical analyses (of groundwater, irrigation water, and soil), water quality indices calculations, statistical analyses, and satellite data. The results revealed high levels of soil salinization in the northern and central areas, with 64% of soil samples classified as strongly and very strongly saline. Soil chemistry indicated salinization sources linked to sodium chloride dominance. Satellite data from Sentinel-2 images and SRTM digital elevation data showed widespread severe waterlogging in the northern lowlands. The Irrigation Water Quality Index (IWQI) values indicated that 87.5% of irrigation water samples posed severe restrictions due to high salinity and sodium hazards, which were mismatched with the low soil permeability observed in 81% of the collected samples exhibiting clay texture and covering most of the study area. Furthermore, shallow groundwater at depths of 0.5-3m with high salinity was detected, where total dissolved solids exceeded 20,000mg/L, and Na-Cl water types prevailed, indicating saltwater intrusion. A strong positive correlation (r > 0.83) was found between shallow saline groundwater and soil salinity. The combination of poor irrigation water quality, shallow saline groundwater tables, and low-permeability soils created a synergistic effect that severely compromised soil health and agricultural productivity. It also posed severe risks to the structural integrity of archaeological sites and buried artifacts through accelerated physical and chemical weathering processes. This necessitates an urgent mitigation strategy to combat soil degradation in this critical area.

Pulses as a Key Component in Conservation Agriculture: Impacts on Soil Health and Sustainability

Intensive agriculture poses several challenges such as soil degradation, reduced soil organic matter, and increased soil nutrient imbalances including nitrogen, phosphorus, potassium, sulfur, zinc, iron, and manganese deficiencies and nutrient toxicities (Tiwari KN, 2002). It also contributes to degradation of groundwater quality, declining groundwater levels (Humphreys E et al, 2010), and issues like sodicity and salinization (Tiwari VM et al, 2009), resulting in reduced crop productivity. Many of these limitations can be addressed by adopting conservation agriculture, which supports sustainable productivity while safeguarding natural resources (Sharma AR et al, 2012). Pulses are particularly beneficial in conservation agriculture as they align well with its principles: diversified crop rotations, minimum soil disturbance and continuous soil cover. They serve as a resource-conserving technology that mitigates the adverse impacts of modern agricultural practices.

Groundwater Quality Prediction and Analysis Using Machine Learning Models and Geospatial Technology

The most prominent source of drinking water is groundwater, followed by lakes and reservoirs. Hydrological parameters like temperature, dissolved oxygen, pH, conductivity, ORP, and turbidity often change due to waste dumping into natural drinking water sources, particularly in densely populated areas. As a result, the water quality must be tested before public consumption to ensure healthy living in society. This research collected water samples from 129 wells in the Kanchipuram district in Tamil Nadu, India. An efficient integrated machine-learning-based prediction model has been proposed and modeled to determine the groundwater quality index (GQI). Several machine learning models were used to predict the water’s quality, including the naïve Bayes model, the KNN classifier, and the XGBoost classifier. Water quality predictions in 2024 were made using a combination of classification algorithms and models based on long short-term memory (LSTM) neural networks. The projected water quality characteristics were analyzed using geographical information system (GIS) technology to better understand and visualize the results. The XGBoost classifier model outperforms prior findings in the literature, with an accuracy of roughly 94.6%. The classification and prediction model was validated using collected and tested current data samples from a selected well. The findings were accurate within the 5% error range, promoting sustainability.

Assessment of Groundwater Quality in the Semi-Arid Environment: Implications of Climate Change

The hydrogeochemical properties and evolution of groundwater in the Essaouira syncline basin in northwestern Morocco were investigated in this study, with a total of 447 samples during different campaigns (April 2017, May 2018, March 2019, and July 2020). These samples were analyzed for major ions and stable and radioactive water isotopes (δ2H, δ18O, and 3H). With decreasing rainfall from climate change in Morocco, it is crucial to assess the sustainability of groundwater reserves. This shortage leads to the degradation of water and soil quality. To ensure sustainable water management and preserve the environment in the study area, it is necessary to assess groundwater quality for drinking and irrigation, take precautions, and establish management plans. This study assessed groundwater quality using two water quality index methods (WQI and IWQI). Several natural processes control groundwater mineralization, including the dissolution of evaporite and carbonate minerals, cation exchange phenomena, evaporation, and seawater intrusion. According to the results obtained using the WQI method, all groundwater samples in the study area are generally of poor quality and must be treated before being used for domestic purposes. Based on the results obtained by the IWQI method, the samples are suitable for use as irrigation water, especially for plants resistant to high salinity concentrations. Stable isotope measurements (δ2H and δ18O) indicate that Atlantic precipitation continuously recharges the recharge areas of the Essaouira Basin. Thus, the low values of tritium (3H) in groundwater mean that the freshwater in the Essaouira Basin is ancient.

Geochemical assessment of groundwater quality for domestic, irrigation and industrial purposes: a tool for environmental monitoring and assessment in a semiarid region of eastern Maharashtra, India

Geochemical assessment of groundwater quality for domestic, irrigation and industrial purposes: a tool for environmental monitoring and assessment in a semiarid region of eastern Maharashtra, India

Multi-temporal image analysis of wetland dynamics using machine learning algorithms

Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards, controlling erosion, and providing essential habitats for unique flora and wildlife. Despite their significance, wetlands are facing decline in various global locations, underscoring the need for effective mapping, monitoring, and predictive modeling approaches. Recent advances in machine learning, time series earth observation data, and cloud computing have opened up new possibilities to address the challenges of large-scale wetlands mapping and dynamics forecasting. This research conducts a comprehensive analysis of wetland dynamics in the Thatta region, encompassing Haleji & Kinjhar Lake in Pakistan, and evaluates the efficacy of different classification systems. Leveraging Google Earth Engine, Landsat imagery, and various spectral indices, we assess four classification techniques to derive accurate wetland mapping results. Our findings demonstrate that Random Forest emerged as the most efficient and accurate method, achieving 87% accuracy across all time periods. Change detection analysis reveals a significant and alarming decline in Haleji & Kinjhar Lake wetlands over 1990–2020, primarily driven by agricultural expansion, urbanization, groundwater extraction, and climate change impacts like rising temperatures and reduced precipitation. If left unaddressed, this continued wetland loss could have severe implications for aquatic and terrestrial species, water and soil quality, wildlife populations, and local livelihoods. The study predicts future wetland dynamics under different scenarios - enhancing drainage for farmland conversion (10–20% increase), increasing urbanization (10–20% expansion), escalating groundwater extraction (7.2m annual decline), and climate change (up to 5 °C warming and 54% precipitation deficit by 2050). These scenarios forecast sustained long-term wetland deterioration driven by anthropogenic pressures and climate change. To guide conservation strategies, the research integrates satellite data analytics, machine learning algorithms, and spatial modeling to generate actionable insights into multifaceted wetland vulnerabilities. Findings provide a robust baseline to inform policies ensuring sustainable management and preservation of these vital ecosystems amidst escalating human and climate threats. Over 1990–2020, the Thatta region witnessed a 352.8 sq.km loss of wetlands, necessitating urgent restoration efforts to safeguard their invaluable ecosystem services.

Geoenvironmental determinants influencing chronic kidney disease of unknown etiology in the dry zone of Sri Lanka: a study based on a cohort of at-risk communities.

Chronic kidney disease of unknown origin (CKDu) has emerged as a serious health risk for farming communities in remote semi-arid lowland regions of Sri Lanka, with geoenvironmental factors widely believed to be associated with the etiology. Although numerous case-control studies have been carried out to determine the causes of CKDu, none have been conducted in at-risk communities. The main objective of this study is to identify the potential geo-environmental risk factors associated with the at-risk community in the Wilgamuwa region, a CKDu endemic area in Sri Lanka. The study collected and analyzed 92 water sources currently or previously used in the study area for major cations, anions, and trace elements, mainly As, Cd, Pd, Mn, Zn, Ba and Sr. The major cations and anions in CKDu-susceptible groundwater varied Si4+ > Ca2+ > Na+ > Mg2+ > K+ and HCO3- > Cl- > SO42- > NO3- > F- > PO43- > Br-. The higher average values of Si4+, F- and total hardness (TH) were reported in groundwater consumed by communities at risk of CKDu, with average values (in mg/L) of Si4+-46, F--0.62, and TH-178. Considering the Water Quality Index (WQI) values, 73% of groundwater sources are classified as poor water quality, and the groundwater quality mainly depends on the fluoride distribution in the region. According to the Hazard Quotient (HQ), the risk of adverse health effects from exposure to F- and SiO2 increased in magnitude in the order of male < female < children. Health hazards due to As, Cd and Pb exposure fell between the 'no-risk' and 'low-risk' categories. As outlined in this study, continuous monitoring of vulnerable communities for environmental exposures to key groundwater constituents is important in the dry zone of Sri Lanka.

Physico-Chemical Analysis of Textile Effluents from Bagru, Jaipur (Rajasthan, India): Implications for Environmental Impact and Treatment Needs

The textile industry is one of the largest water polluters worldwide. The coloured and bad odour effluent discharged from such industries pollutes not only the water bodies but also affects groundwater quality. In the present study, thirty-five water samples were collected from different dyeing units of the Bagru textile area (Rajasthan, India) famous for using natural dyes for textile processing. The physico-chemical analysis of these water samples shows that all parameters exceeded the permitted range recommended by the Central Pollution Control Board (CPCB) and World Health Organization (WHO). The analysis revealed the use of synthetic dyes in Bagru's textile industry for dyeing and printing. Based on the estimated characteristics, these textile effluents must be properly treated before releasing into the environment as the discharge of untreated effluents into local water bodies leads to significant water pollution, adversely affecting aquatic ecosystems and biodiversity. Additionally, contaminants can permeate the soil, compromising agricultural productivity and food safety. The air quality is also compromised due to the release of volatile organic compounds (VOCs) during the dyeing process, posing respiratory risks to nearby communities. This research underscores the urgent need for improved waste management practices and regulatory measures to mitigate the adverse environmental effects associated with synthetic dyes in Bagru's textile industry.

Groundwater quality in Sargodha City, Pakistan: Comprehensive research of geochemical modeling, groundwater quality assessment, and risk evaluation

Groundwater, an indispensable global resource, faces escalating contamination threats, jeopardizing human health and environmental sustainability. This study offers detailed insights into the quality of the groundwater, its drinking suitability, and associated human health risks in Sargodha City, Pakistan. Employing hydrogeochemical analysis, inverse geochemical modeling, groundwater quality index, and human health risk evaluation, this research highlights widespread exceedances of WHO drinking water standards, particularly in TDS, EC, TH, Na+, Ca2+, Mg2+, SO42−, Cl−, HCO3−, NO3–N, and As levels, signifying that a significant portion of the groundwater is unfit for consumption. Hydrochemical facies analysis reveals a dominance of the Na–Cl type. Water–rock interactions, cation exchange, and anthropogenic influences are the primary factors shaping groundwater hydrochemistry in the region. Saturation indices and inverse geochemical modeling demonstrated intricate geochemical processes involving both mineral precipitation and dissolution. Notably, the GWQI reveals a diverse spectrum of water quality, with 50% of the samples exhibiting excellent to good quality, 29% falling into the poor to extremely poor category, and 21% deemed unfit for drinking. Health risk assessment reveals alarming carcinogenic risks from As, affecting children (70.8%) and adults (83.35%), while 8.3% of the samples indicate non-carcinogenic risks. Conversely, NO3–N presents acceptable non-carcinogenic risks across all samples. The total hazard index spans between 0.14 and 1.90 for adults and 0.16 to 2.23 for children, underscoring the heightened vulnerability of children. This study advances the understanding of groundwater contamination dynamics in urbanized regions, offering insights to safeguard public health and ensure sustainable water management in areas with similar hydrogeochemical conditions.

Assessment of Groundwater Quality Under Unplanned Urban Environment: a Case Study From Vellore City, Tamilnadu, India

Assessment of Groundwater Quality Under Unplanned Urban Environment: a Case Study From Vellore City, Tamilnadu, India

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches

Seasonal spatial distribution of groundwater suitability in the Cabo Frio shallow coastal aquifer, Rio de Janeiro, Brazil: applying groundwater quality index and GIS approaches