Evaluation Of Groundwater Quality Research Articles

Hydrochemical and Formation Mechanism Studies of Groundwater in Quaternary Aquifer in a Northern Plain of China: An Example of Beijing Plain

Beijing Plain is a very active part of Beijing city regarding the socio-economic and human activities of the region. Over the past four decades, Beijing’s economic development and the continuous drought for nearly 10 years in the 2000s have negatively impacted the groundwater quantity and quality. Therefore, it is necessary to investigate the present situation of groundwater chemistry in this region to develop a comprehensive database and orientation for future research on groundwater quality evaluation. Mathematical statistics, Piper’s trilinear diagram, Gibbs plots, the ion ratio method and PHREEQC software 3.7.3 were used to analyze the groundwater hydrogeochemical characteristics and formation mechanisms of the quaternary aquifers of the Beijing Plain area. Hydrogeochemical results indicated that the groundwater is slightly alkaline, with pH values ranging from 6.76 to 8.65 and an average value of 7.92. The order of major cations in groundwater was Ca2+ > Na+ > Mg2+ > K+ with average values of 66.54 mg/L, 50.58 mg/L, 23.78 mg/L, and 1.81 mg/L, respectively, while the order of major anions was HCO3− > SO42− > Cl− with average values of 284.89 mg/L, 52.1 mg/L and 35.5 mg/L, respectively. The groundwater chemical types are Mg-Ca-Cl-HCO3, Na-Ca-HCO3, Mg-Ca-HCO3 and Mg-Na-HCO3. Research on the main influencing factors and PHREEQC hydrogeochemical inverse simulations results along the four pathways selected confirmed that rock weathering with sulfate, silicate and carbonate rock mineral dissolution and Na+, Mg2+ and Ca2+ ion reaction exchange influenced groundwater hydrogeochemical characteristics of the quaternary aquifers of the Beijing Plain area. Understanding the formation mechanisms of hydrogeochemistry in quaternary plains provides guidance for future studies and, through suggestions and case studies, facilitates decision-making by policy-makers on the sustainable management of groundwater resources.

Enhancing Groundwater Quality Evaluation Using Associative Rule Mining Technique with Random Forest Split Gini Indexing Algorithm for Nitrate Concentration Analysis

Human actions and changing weather patterns are contributing to the growing demand for groundwater resources. Nevertheless, evaluating the quality of groundwater is crucial. Nitrate is a significant water contaminant that can lead to blue-baby syndrome or methemoglobinemia. Therefore, it is necessary to assess the level of nitrate in groundwater. Current methods involve evaluating the quality of groundwater and integrating it into the models. The inappropriate datasets, lack of performance, and other constraints are limitations of current methods. Ground water dataset is used and pre-processed the data’s. Selected data’s are feature extracted and associated with the rule ranking. In the suggested model, the use of associative rule mining technique has been implemented to address these challenges and assess nitrate levels in groundwater. The method of rule ranking is carried out using association rule mining technique to divide the datasets. The split gini indexing algorithm is introduced in the proposed model for data classification. The Split Gini Indexing algorithm is a decision tree induction algorithm that is used to build decision trees for classification tasks. It is based on the Gini impurity measure, which measures the heterogeneity of a dataset. The quality of groundwater has been classified using Naïve Bayes, SVM, and KNN algorithms. The proposed approach's efficiency is evaluated by calculating performance metrics such as precision, accuracy, F1-score, and recall values. The suggested method in the current research attains an improved accuracy of 0.99, demonstrating enhanced performance.

Hydrochemical Characteristics and Water Quality Evaluation of Groundwater in the Luohe Formation of Binchang Mining Area, China

Hydrochemical Characteristics and Water Quality Evaluation of Groundwater in the Luohe Formation of Binchang Mining Area, China

Four Optimization Meta-heuristic Approaches in Evaluating Groundwater Quality (Case study: Shiraz Plain)

Four Optimization Meta-heuristic Approaches in Evaluating Groundwater Quality (Case study: Shiraz Plain)

Evaluation of River and Groundwater Quality in the Mzimvubu to Tsitsikamma Water Management Area (WMA7)

This paper assessed and evaluated the river and groundwater quality of five major catchments in the Mzimvubu to Tsitsikamma Water Management Area (WMA7). The river assessment and evaluation considered the present state maximum, minimum and mean seasonal values of physiochemical parameters (EC, NO3 + NO2, Cl, pH, NH4-N, PO4-P and Mg). The study was able to successfully make use of statistical analysis and a water quality index in order to explain seven-year trends and the present state of all five catchments within the study area. The statistical analysis results showed that water quality parameters such as PO4, NH4 and NO3 + NO2 were not complying with the South African Water Quality Guidelines (SAWQG) limits, suggesting that the study area was impacted by anthropogenic activities such as agriculture, sewage works, etc. The application of WQI showed that the Gamtoos catchment was in a good water quality state (49.71) while the other four catchments were in a poor to very poor state, according to the WQI classification. Based on the groundwater quality assessment, the physicochemical parameters (NH4, EC, Ca, NO3 + NO2, pH, Na, Cl, Mg, F, K, SO4 and CaCO3) were selected and the main parameters of concern were EC (salinity), NO3 + NO2 and SO4. However, groundwater assessment revealed that groundwater quality was chemically suitable for drinking purposes in most parts of the study area. Therefore, the study recommended resource-directed measures to improve surface and groundwater resource protection, especially in areas where surface and groundwater quality for other uses remains a challenge. Further, strong water resource compliance monitoring and enforcement to control water resource pollution sources is critical.

Hydrogeochemical Evaluation of Groundwater Quality and Its Applicability for Various Purposes in the Drought-Prone Konso Zone, Rift Valley, Southern Ethiopia

The present study area, the Konso Zone, is in Rift Valley, Southern Ethiopia, and highly depends on rivers and groundwater for economic and social development. Water availability in this area faces multiple challenges, including scarcity, quality concerns, and seasonal variations. In the Rift Valley region, including the present study area, groundwater quality is particularly problematic due to high fluoride levels. Moreover, the high concentrations of total dissolved solids in Konso Zone groundwater pose challenges for industrial, agricultural, and drinking purposes. GIS-based spatial analysis techniques, hydrogeochemical analyses, and water quality indices were used in the current study. The evaluation of water quality involved the utilization of both groundwater quality and irrigation water quality indices. In the study area, the cations and anions exhibited a general trend with Na+ > Mg2+ > Ca2+ > K+ > Fe2+ and HCO3− > Cl−, SO42− > NO3− > F−. Multiple water types were identified within the research area, including Na-HCO3, Ca-Na-HCO3, NaCl, and Ca-Mg/Cl, with Na-HCO3 being the most prevalent. The formation of the NaHCO3 water type is primarily attributed to ion exchange processes, with siliciclastic aquifers being linked to cation exchange in sodium bicarbonate groundwater. Total Dissolved Solids and SO42− contaminants significantly impact the water quality, resulting in deterioration. Gibbs’s figure indicates that 50% of the water samples were found where rocks were weathered, demonstrating the importance of water-rock interactions in groundwater composition. Water samples containing more fluoride than the WHO’s limit of 1.50 mg/L were deemed unsuitable for consumption. Regarding irrigation suitability, most water samples from the Konso area were acceptable, except for the sodium percentage in 66.6% of the samples, which was unsuitable for irrigation. There are 26.67% of samples that are of questionable quality, 66.67% that are deemed inappropriate, and 26.67% that are deemed unacceptable. These findings underscore the pressing need for comprehensive strategies and interventions to address water quality issues in the Konso Zone, emphasizing the critical importance of monitoring and managing groundwater resources to ensure sustainable and safe water access for various regional uses.

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model.

An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks of nitrate were revealed by the integrated approaches of self-organizing map analysis, spatial visualization by geography information system, entropy and irrigation water quality indices, and human health risk model. Groundwater samples were categorized into two clusters by SOM analysis. Cluster I including three samples were Ca-SO4 type and cluster II of remaining 136 samples were Ca-HCO3 type. Hydrochemical compositions of two cluster samples were dominated by water-rock interaction: (1) calcite and gypsum dissolution for cluster I samples and (2) calcite dissolution, silicate weathering, and positive cation exchange for cluster II samples. Nitrate contamination occurred in both cluster I and II samples, primarily induced by agricultural nitrogen fertilizer. The EWQI results showed that 90.97% in total groundwater samples were suitable for drinking purpose, while the IWQI results demonstrated that 65.03% in total groundwater samples were appropriate for irrigation purpose. The HHR model and Monte Carlo simulation indicated that the non-carcinogenic nitrated risk was highest in children. Exposure frequency was the most sensitive factor (86.33% in total) influencing the total non-carcinogenic risk, indicated by sensitivity analysis. Compared with the two clusters of groundwater, surface water has a shorter circulation cycle and lower ion concentrations resulting in better water quality. This study can provide scientific basis for groundwater quality evaluation in other parts of the world.

Geochemical Evaluation of Groundwater Quality in the Coastal Aquifers of Kujang Block, Jagatsinghpur District, Eastern Odisha, India

Geochemical Evaluation of Groundwater Quality in the Coastal Aquifers of Kujang Block, Jagatsinghpur District, Eastern Odisha, India

Hydrochemical characteristics assessment and evaluation of groundwater quality through MSTs and irrigation indices

Hydrochemical characteristics assessment and evaluation of groundwater quality through MSTs and irrigation indices

Hydrogeological assessment and contaminant transport modelling of Enyimba landfill site in Aba, Nigeria

ABSTRACT Commercial and industrial growth in cities generates hazardous waste, often disposed of in open dump sites, contaminating groundwater. Understanding pollutant movement and numerical models are crucial for effective water resource management. This study assessed hydrogeological dynamics and pollutant transfer in the Enyimba landfill site, Nigeria, using field surveys and contaminant modelling to understand groundwater quality and arsenic contamination spread. The research technique included field and laboratory experiments, as well as water sampling during both dry and wet seasons, to evaluate groundwater quality. The geochemical examination of groundwater samples revealed the amounts of several metals using atomic absorption spectrophotometry. The study used contaminant transport modelling with Visual MODFLOW Flex 6.1 and MT3DMS software to simulate groundwater flow and solute transport within the aquifer layers. Predictive simulations over a 20-year timeframe demonstrated the progressive spread of arsenic pollution from the landfill, resulting in an ellipsoid-shaped plume stretching from its source. Arsenic levels have gradually increased, posing a serious threat to groundwater quality and human health. The research highlights the need for remedial measures to reduce groundwater pollution, including waste recovery and recycling facilities and geo-membrane use. It emphasizes proactive actions to protect groundwater supplies and promote environmental sustainability in the Enyimba landfill site.

Space-temporal analysis of groundwater quality in three areas of the state of Yucatán, México, and its relationship with existing anthropogenic activity.

Groundwater in the Yucatan State is the only source of water. The karst aquifer in Yucatan is vulnerable to pollution. Anthropic activities in Yucatan, such as pig farming, are usually related to high wastewater discharges and water pollution. Administrative and logistical issues in developing on-site sampling to evaluate water quality are common in Mexico. The RENAMECA database provides official data related to groundwater quality. However, no analysis based on this database has been reported. A groundwater quality evaluation based on five reference pig farms and the effect of spatial and temporal anthropic activities in the study area was developed. Eighteen wells based on their location concerning the selected pig farms were studied. On-site sampling and laboratory analysis of the supply water and wastewater in the study case farm were done. Fecal coliforms (FC) values (maximum 2850 MPN [100mL] -1) in most cases for supply water wells exceeded the allowed limit by NOM-127-SAA1-2021. The year of monitoring was significant (P < 0.05) on FC concentrations. Population density and the proximity of wells to population centers affect negatively the presence of total dissolved solids (TDS) and total nitrogen (TN). TDS (maximum value 2620mg L -1) and phosphorus presence could be related to agricultural activities, human settlements, and local aquifer conditions. A local wastewater treatment issue is evident. Groundwater is not quality for consumption without treatment. Regarding the issues in on-site water monitoring, database analysis provides an approximation of the real situation of groundwater quality.

Groundwater quality evaluation for drinking and irrigation using analytical hierarchy process with GIS in semi critical block of Chhattisgarh, India

Groundwater quality evaluation for drinking and irrigation using analytical hierarchy process with GIS in semi critical block of Chhattisgarh, India

Assessing groundwater quality in semi-arid conditions: a geographic information systems-integrated approach using water quality index

Meeting freshwater demands in water-scarce regions is imperative, given challenges like hydric stress, urbanization, aridity, and population growth. This study focuses on the Tebessa aquifer system, a critical water source facing escalating demands. A primary objective is to identify actionable management strategies to improve groundwater quality dynamics in semi-arid regions. The methodology involves a comprehensive assessment of groundwater health using the Water Quality Index (WQI) approach. This method integrates diverse parameters influenced by intensive agricultural and industrial activities. Additionally, spatial relationship analysis, facilitated by Geographic Information System (GIS) technology, is employed to gain insights into complex hydrogeological processes. The multi-parameter strategy implemented results in water quality maps that highlight various ions, revealing spatial disparities and assigning quality priority classes from 'Good' to 'Poor' across the groundwater. The research, conducted in the semi-arid Tebessa-Morsott Plain, encompasses field and laboratory investigations to delineate hydrochemical traits, including alkalinity, salinity, and heightened ion concentrations. The results of the study contribute to scientific understanding by uncovering interrelationships and spatial intricacies, offering valuable insights for water resource governance. The effectiveness of the methodology, incorporating WQI and GIS, is demonstrated in the comprehensive evaluation of groundwater quality. Ultimately, this research provides a foundation for informed decision-making and sustainable management of groundwater resources in semi-arid regions.

Spatial and seasonal groundwater quality assessment for drinking suitability using index and machine learning approach

Spatial and seasonal evaluation and monitoring of groundwater (GW) quality is essential for the sustainable management of this priceless resource and the provision of safe drinking water. Nevertheless, GW quality appraisal was not given due attention in the current study area (flat terrain part of the Tana sub-basin). This study sought to assess the seasonal and regional physicochemical GW quality parameters for drinking appropriateness using the drinking water quality index (DWQI) and support vector machine (SVM). The main cations in both the dry and wet study seasons were, in decreasing order, Na+, Ca2+, Mg2+, K+, and Fe2+, according to the results. Conversely, the main anions were HCO3−, CO32−, Cl− or NO3−, SO42− and PO43−, ordered from higher to lower. During the two research seasons, Ca–HCO3 and Na–HCO3 were the predominant water types based on Piper diagram results. Reverse ion exchange and evaporation were the principal hydrogeochemical processes that control the hydrogeochemistry identified by Durov and Gibbs diagrams, respectively. Excellent GW quality class for drinking was demonstrated by the majority of geographical and seasonal DWQI readings over the two seasons. Nevertheless, during the rainy season, there was a noticeable decline in the GW quality condition around the northern shores of Lake Tana. Therefore, it is advised to implement comprehensive GW quality protection measures and improve system management to mitigate pollution to reduce health hazards in the examined region.

Application of bioassays and physicochemical analysis for assessing groundwater quality of selected tube wells in a CKDu impacted area

Groundwater from tube and dug wells are primarily used for drinking purposes by rural communities inhabiting Chronic Kidney Disease of unknown aetiology (CKDu) impacted areas in Sri Lanka. Groundwater safety assessment using targeted physicochemical analysis alone is not adequate to capture interactive effects of chemical mixtures in the groundwater. This study explored for the first time combined use of physicochemical analysis and bioassays with root meristems of Allium cepa and erythrocytes of Cyprinus carpio to assess groundwater quality of selected tube wells in Medawachchiya (a CKDu impacted area), Sri Lanka covering pre-monsoon, monsoon and postmonsoon seasons. The pH, turbidity, arsenic, cadmium, lead, mercury, fluoride, chloride, nitrate and nitrite levels in the groundwater complied with Sri Lanka standards for potable drinking water in all seasons. Yet, alkalinity and total hardness levels in the groundwater exceeded national drinking water standards (nearly up to two folds) mostly in the monsoon season. Bioassays revealed genotoxic effects of the groundwater of some tube wells in pre-monsoon and monsoon seasons. Observed genotoxicity may be associated with synergistic effects of contaminants including undetected and unknown chemicals in the groundwater depending on the season. The results support the use of bioassays as complementary tools for evaluating groundwater quality of CKDu hotspots considering consumer safety.

Geospatial evaluation of groundwater quality in an industrialized district of Haryana, India, using an integrated approach

Geospatial evaluation of groundwater quality in an industrialized district of Haryana, India, using an integrated approach

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand

Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore the applicability of random forest (RF) and artificial neural networks (ANN) models to predict groundwater quality. Particularly, these two models were integrated into cross-validation (CV) and bootstrapping (B) techniques to build predictive models, including RF-CV, RF-B, ANN-CV, and ANN-B. Entropy groundwater quality index (EWQI) was converted to normalized EWQI which was then classified into five levels from very poor to very good. A total of twelve physicochemical parameters from 180 groundwater wells, including potassium, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, nitrate, pH, electrical conductivity, total dissolved solids, and total hardness, were investigated to decipher groundwater quality in the eastern part of Kanchanaburi Province, Thailand. Our results indicated that groundwater quality in the study area was primarily polluted by calcium, magnesium, and bicarbonate and that the RF-CV model (RMSE = 0.06, R2 = 0.87, MAE = 0.04) outperformed the RF-B (RMSE = 0.07, R2 = 0.80, MAE = 0.04), ANN-CV (RMSE = 0.09, R2 = 0.70, MAE = 0.06), and ANN-B (RMSE = 0.10, R2 = 0.67, MAE = 0.06). Our findings highlight the superiority of the RF models over the ANN models based on the CV and B techniques. In addition, the role of groundwater parameters to the normalized EWQI in various machine learning models was found. The groundwater quality map created by the RF-CV model can be applied to orient groundwater use.

Integrated GIS-based and water quality index for evaluation of groundwater quality in the coastal slum settlements of Lagos, Nigeria

This study aimed to identify drinking water suitability through a statistical and water quality index (WQI) approach in coastal slum settlements in Lagos, Nigeria. A total of 250 borehole groundwater samples collected for drinking purposes during the wet (125) and dry (125) seasons were analysed for their physical and chemical properties from 2019 to 2020. The physical and chemical characterisation of the region was conducted based on the correlation matrix, scree plot, PCA, Q-mode HCA, and ROC curve to identify the types of weathering, the influence of rock on precipitation and evaporation, and types of reactions that affect groundwater composition. The analytical mean concentration results revealed that SO4, Cl, TH, NO3, TDS, and PO4 surpassed the USEPA and WHO permissible limits in both seasons. The WQI results demonstrate that 7.6% and 6.7% of water samples fall into the excellent category, while 12.4% and 11.5% are moderately tolerable. In contrast, for both seasons, >100% of the samples fell into the unsuitable drinking category across SA1-SA5, SB1-SB5, SC1-SC5, SD1−SD5, and SE1−SE5. Groundwater quality mainly deteriorates due to anthropogenic activities and climatic variability. The spatial variation map indicates that groundwater quality is primarily affected during the wet season and, to a lesser extent, in a few slums during the dry season. Seawater influx in coastline areas has been identified as the main factor threatening the quality and availability of groundwater resources. As a result, the groundwater quality is mostly poor to unsuitable, and this study confirms its unsuitability for drinking. Hence, this study serves as a guide for effective action in sustainable groundwater management.

Evaluation of groundwater quality for irrigation purposes in hard rock terrain of Southern India using water quality indices modelling

Industrial effluent discharge threatens both agricultural productivity and drinking water quality by depleting groundwater, contaminating surface water and demanding high-quality irrigation water. This study evaluates the influence of urbanization and agricultural activities on the groundwater quality in Perundurai, focusing on its suitability for both drinking and agriculture. A total fourty samples of groundwater were randomly taken from bore wells. The principal cations and anions were analyzed revealed their dominance order: Na Ca > Mg > K and Cl > SO4 > F > NO3. The water quality index (WQI) analysis found that around 89% samples are unsuitable for drinking. The PI value indicates that 2% samples have poor permeability and elevated risk of waterlogging make it unsuitable for field use. Analysis of the Piper diagram reveals the dominance of alkaline earth cations (Ca, Mg) over alkali metals (Na, K) and weak acids (HCO3, CO3) over strong acids (Cl, SO4), indicating specific hydrogeochemical facies. From the US salinity diagram (USSL), C4S1 samples (30%) exhibit low alkalinity but a hazardous high salinity which impairs their capacity to retain water. Wilcox classification identified that 27% samples exhibit potential limitations for irrigation due to elevated sodium content. Contamination of groundwater due to ion leaching, sewage discharge and runoff is a significant environmental concern with potential health implications.

Evaluation of Groundwater Quality Throughout the Seasons in the Rahata Tahsil District of Ahmednagar, Maharashtra, India

Evaluation of Groundwater Quality Throughout the Seasons in the Rahata Tahsil District of Ahmednagar, Maharashtra, India