Variation Of Groundwater Quality Research Articles

Groundwater Quality Variations in Multiple Aquifers: A Comprehensive Evaluation for Public Health and Agricultural Use

Understanding hydrological and hydrochemical processes is crucial for the effective management and protection of groundwater resources. This study conducted a comprehensive investigation into hydrochemical processes and variations in groundwater quality across five distinct aquifers in Phra Nakhon Si Ayutthaya, Thailand: Bangkok (BKK), Phra Pradaeng (PPD), Nakhon Luang (NKL), Nonthaburi (NTB), and Sam Khok (SK). Utilizing various diagrams, the findings revealed that high levels of sodium and salinity in shallow aquifers (BKK and PPD) were found which can impede soil permeability and have potential consequences on crop yields. The presence of four distinct types of groundwater—Na-Cl, Na-HCO3, Ca-Cl, and Ca-HCO3—suggests the influence of rock weathering, mineral dissolution, and ion exchange reactions with the surrounding geological formations, controlling the chemistry in the groundwater basin. The research also highlights concerns regarding groundwater quality, particularly elevated concentrations of heavy metals (e.g., Zn, Hg, Pd, Fe, and Mn) exceeding safe drinking water guidelines established by the World Health Organization (WHO) in certain samples. The evaluation of water suitability for consumption and irrigation using the Water Quality Index (WQI) and Wilcox diagram reveals a predominance of “poor” or “unsuitable” categorizations. Untreated sewage discharge and fertilizer usage were identified as the primary anthropogenic activities affecting hydrochemical processes in groundwater. These findings emphasize the need for continuous monitoring, appropriate management, and remediation efforts to mitigate potential hazards.

Impact of mine closure on groundwater resource: Experience from Westrand Basin-South Africa

The mining sector is at the edge of expanding to cater for natural resources that are much needed for technological development and manufacturing. Mushrooming of mines will consequently increase the number of mines closure. Moreover, mines closure have adverse impact on the environment at large and specifically on water resources. This study analyses historical groundwater quality parameters in mine intensive basin of Westrand Basin (WRB) to understand the status of groundwater quality in relation to mining activities and mine closure. Geographic information system (GIS) was used to map the spatio-temporal variation of groundwater quality in the basin and groundwater quality index (GQI) to evaluate its status. The coefficient of variation (CV) was applied to understand the stability of groundwater quality after the mine closure. Results indicated unstable and altered trend with increasing levels of acidity and salts concentration around the mines vicinity following the mine closure. The resultant maps indicated a significant deterioration of groundwater quality around the WRB with concentrations decreasing downstream. Obtained average GQI for the study period of 1996–2015 suggested a moderate groundwater quality at a range of GQI = 64–73. The CV indicated varying water quality at CV > 30% suggesting presence of source of contamination. Observed groundwater quality trends in Westrand basin suggested that mines closure present potential threat on groundwater quality and thus, a need for a robust mine closure plan and implementation.

Evaluation of Seasonal a Spatial Variation of Groundwater Quality by Determining Factors Associated with Water Quality Using Multivariate Analytical Methods, Erbil Central Sub-Basin

The study area is located in the northern Iraqi province of Erbil, covering a total area of about 1400 Km2 (3.5% of Iraq). The Erbil basin is mostly covered by Quaternary sediments, with only a few outcrops of Miocene–Pliocene formations in the east and northeast of Sharabot-Dedawan highlands, Avanah Mountain in the west and southwest in narrow strips, and Damirdagh in the north. The lithology of sediments ranges from clay, silt, sand, and gravel (sandstone, clay stone, and conglomerate). Erbil Basin, also known as Dashty Hawler Basin, Erbil provinces is the largest groundwater reservoir, with a surface area of 3200 Km2 and a depth of approximately 800 meters. Erbil Basin, one of the Middle East's most important groundwater basins, is bounded on the north by the Greater Zab River and on the south by the Lesser Zab River. Thirty water samples (27 samples of groundwater wells, and 3 samples of wastewater channels) were collected during May (Water surplus period) and September (Water deficit period) 2020 in Erbil central sub-basin and analyzed. Physical analyses include temperature (T), pH, Electrical Conductivity (EC), Total Dissolved Solids (TDS), Biological Oxygen Demand (BOD5), Chemical oxygen demand (COD), Dissolved oxygen (DO), Total Suspension sediments (TSS), whereas the geochemical analysis included concentration determination of the major, minor and trace elements. This article aims to evaluate the pollution in groundwater of the Erbil central sub-basin due to different kinds of wastewater, the samples of water in the study area were collected from different locations and sources, deep wells, and waste. all chemical, physical, and trace elements parameters are presented in this work, the pollution has been founded in the study area due to waste water by Kahrez (old groundwater distribution in Erbil basin), cesspools, and septic tanks.

Ant Colony Based Artificial Neural Network for Predicting Spatial and Temporal Variation in Groundwater Quality

The quality of groundwater is of utmost importance, as it directly impacts human health and the environment. In major parts of the world, groundwater is the main source of drinking water, hence it is essential to periodically monitor its quality. Conventional water-quality monitoring techniques involve the periodical collection of water samples and subsequent analysis in the laboratory. This process is expensive, time-consuming and involves a lot of manual labor, whereas data-driven models based on artificial intelligence can offer an alternative and more efficient way to predict groundwater quality. In spite of the advantages of such models based on artificial neural network (ANN) and ant colony optimization (ACO), no studies have been carried out on the applications of these in the field of groundwater contamination. The aim of our study is to build an ant colony optimized neural network for predicting groundwater quality parameters. We have proposed ANN comprising of six hidden layers. The approach was validated using our groundwater quality dataset of a hard rock region located in the northern part of Karnataka, India. Groundwater samples were collected by us once every 4 months from March 2014 to October 2020 from 50 wells in this region. These samples were analyzed for the pH, electrical conductivity, Na+, Ca+, K+, Mg2+, HCO3−, F−, Cl− and U+. This temporal dataset was split for training, testing and validation of our model. Metrics such as R2 (Coefficient of Determination), RMSE (Root Mean Squared Error), NSE (Nash–Sutcliffe efficiencies) and MAE (Mean Absolute Error) were used to evaluate the prediction error and model performance. These performance evaluation metrics indicated the efficiency of our model in predicting the temporal variation in groundwater quality parameters. The method proposed can be used for prediction and it will aid in modifying or reducing the temporal frequency of sample collection to save time and cost. The study confirms that the combination of ANN with ACO is a promising tool to optimize weights while training the network, and for prediction of groundwater quality.

Hydrogeochemical Evaluation of Groundwater for Drinking and Irrigation Purposes in the Upper Piedmont Area of Haridwar, India

In this study, the suitability of groundwater quality for the purpose of drinking and irrigation was evaluated in the upper piedmont area of Haridwar, India. In this regard, inverse distance-weighted interpolation, water quality index (WQI), principal component analysis (PCA), piper trilinear diagram (PTD) analysis, and sodium absorption ratio (SAR) methods were used to assess the geospatial variation of groundwater quality. The results showed that groundwater was partially affected by rapid industrialization and urbanization practices. The groundwater quality revealed the presence of different cations and anions in the following order: Ca2+ > Na+ > Mg2+ > K+ and HCO3– > NO3– > SO42– > Cl– > SiO2– > F–. WQI showed an excellent range (29.94–45.17) for sampling sites S1–S3 and S5–S8 and a good value for site S4 (99.2). In addition, PTD confirmed that the calcium and magnesium bicarbonate type and mixed type for groundwater while PCA revealed that nitrate was dominant at site S4. In addition, the SAR and Na contents were in excellent ranges, indicating their suitability for irrigation purposes. The outcomes of this study indicated that geogenic and anthropogenic processes were the major reasons for the change in groundwater quality of this region.

Hydrogeochemical assessment of groundwater quality for drinking and irrigation applying groundwater quality index (GWQI) and irrigation water quality index (IWQI)

In recent times, the contamination of groundwater in the extended part of Chota Nagpur Plateau becomes a big concern. The demand of high-quality drinking and irrigation water has been significantly augmented. Consequently, productivity and fertility of soils are being reduced in the recent years due to use of low quality irrigation water. Thus, it is crucial to know the groundwater quality for the appropriate planning and management of groundwater resources to determine its use for drinking and irrigation purposes. Therefore, the principal objectives of this study are (i) to evaluate the magnitude and spatial variations of groundwater quality using the Groundwater Quality Index (GWQI) for drinking and (ii) to examine the irrigation suitability of groundwater using irrigation water quality index (IWQI). Sodium absorption ratio (SAR), Soluble sodium percentage (SSP), Magnesium hazard (MH), Kelly's index (KI), Permeability Index (PI) have been applied for suitability of irrigation water. Result showed that in 2021, GWQI values vary from 51.75 to 171.18 and seven blocks of the Purulia district among twenty blocks have poor drinking water quality while in 2022 it ranges from 70.27 to 178.45 and eight blocks stand poor water quality. In terms of irrigation water quality, Purulia II and Hura blocks come under the ‘doubtful’ or ‘poor ‘categories in pre and post-monsoon seasons for both the years. Hydro-chemical facies through Piper, USSL and Durov's diagram showed medium to high salinity and low to medium sodium hazards in this region. Feldspar and biotite minerals of granite and gneiss accelerate the bicarbonate and chloride ions in groundwater. Non point sources are also responsible for water quality deterioration in this agricultural dominated region. These research findings will help to policy makers and administrators for the management of groundwater resources and agricultural sustainability particularly in the dryland region.

Temporal and Spatial Analysis of the Groundwater Quality Variations in Faradonbeh Plain and Evaluation of Its Usability for Agricultural Uses During 1991-2019

Temporal and Spatial Analysis of the Groundwater Quality Variations in Faradonbeh Plain and Evaluation of Its Usability for Agricultural Uses During 1991-2019

Climate variability and changes in shallow groundwater quality on Indonesia’s small tropical island

Climate variability and changes in shallow groundwater quality on Indonesia’s small tropical island

Exploring Multiscale Variability in Groundwater Quality: A Comparative Analysis of Spatial and Temporal Patterns via Clustering

Defining homogeneous units to optimize the monitoring and management of groundwater is a key challenge for organizations responsible for the protection of water for human consumption. However, the number of groundwater bodies (GWBs) is too large for targeted monitoring and recommendations. This study, carried out in the Provence-Alpes-Côte d’Azur region of France, is based on the intersection of two databases, one grouping together the physicochemical and bacteriological analyses of water and the other delimiting the boundaries of groundwater bodies. The extracted dataset contains 8627 measurements from 1143 observation points distributed over 63 GWB. Data conditioning through logarithmic transformation, dimensional reduction through principal component analysis, and hierarchical classification allows the grouping of GWBs into 11 homogeneous clusters. The fractions of unexplained variance (FUV) and ANOVA R2 were calculated to assess the performance of the method at each scale. For example, for the total dissolved load (TDS) parameter, the temporal variance was quantified at 0.36 and the clustering causes a loss of information with an R2 going from 0.63 to 0.4 from the scale of the sampling point to that of the GWB cluster. The results show that the logarithmic transformation reduces the effect of outliers and improves the quality of the GWB clustering. The groups of GWBs are homogeneous and clearly distinguishable from each other. The results can be used to define specific management and protection strategies for each group. The study also highlights the need to take into account the temporal variability of groundwater quality when implementing monitoring and management programs.

Groundwater quality assessment for drinking purposes: a case study in the Mekong Delta, Vietnam

Groundwater serves as an important resource for people in the Mekong Delta, but its quality has been continuously declined from human activities. Current status of the groundwater quality needs to be evaluated for sustainable groundwater resource management. This study aimed to evaluate the groundwater quality for drinking purposes in the Mekong Delta, Vietnam, using multivariate statistical methods and integrated-weight water quality index. Data comprised 8 water quality parameters (pH, total hardness, nitrate (NO3−), iron (Fe), lead (Pb), mercury (Hg), arsenic (As), and coliforms) obtained from 64 observation wells in An Giang province, Dong Thap province, and Can Tho city, were analyzed by cluster analysis (CA), principal component analysis (PCA), and integrated-weight water quality index (IWQI). The results indicated that most parameters were within standards while excessive hardness and Fe contamination were found in some regions. More than 80% of samples were detected with serious coliform contamination. The CA results revealed that groundwater quality heavily depend on geological locations with 4 clusters of the sampling locations. Three principal components obtained from PCA could explain 77.2% of the groundwater quality variation. The IWQI values ranging from 4 to 2761 classified groundwater quality as excellent (53.1%), good (25%), poor (9.4%), very poor (4.7%), and undrinkable (7.8%), which were associated with coliform contamination. These findings have provided insights into the groundwater quality status in the region, which can benefit in developing a water protection strategy.

Spatial-temporal Variation in Groundwater Quality and the Contamination Source Analysis in Shihezi-Changji Area

To analyze spatial-temporal variation in groundwater quality and contamination sources in the Shihezi-Changji area in Xinjiang, a Bayesian water quality evaluation model based on Shannon entropy, Spearman rank correlation coefficient, principal component analysis, and an absolute principal component scores-multiple linear regression receptor model (APCS-MLR) were comprehensively used in this study. Groundwater samples in 23 in-situ wells were collected from 2016 to 2021 for quality analysis. The results showed that ① groundwater quality was generally good, with most samples having a phreatic water quality of Class Ⅰ and Class Ⅱ and most confined groundwater quality being of Class Ⅰ. ② Temporally, 2016 and 2017 were the key time nodes of water quality variation in phreatic water and confined groundwater, respectively. Class Ⅳ and Class Ⅴ groundwater was observed only before the key time nodes, whereas after those time nodes the groundwater quality fluctuated within Class Ⅰ to Class Ⅲ. ③ Spatially, the order of phreatic water quality in descending order was Shihezi City, Hutubi county, Manas county, and Changji City, whereas that of confined groundwater quality was:Shihezi City and Changji City, Hutubi county, and Manas county. ④ The spatial-temporal variations in groundwater quality and that in major related indices were basically similar and highly heterogeneous. ⑤ Phreatic water quality was mainly affected by leaching (67.30%), leaching-migration (10.89%), and agricultural-domestic pollution (9.44%); by contrast, unconfined groundwater quality was mainly affected by leaching-enrichment (52.08%), agricultural-domestic pollution (16.06%), and ion exchange under an alkaline environment (12.64%). Although groundwater quality was improved over the years, more attention should be paid to groundwater salinization in the 149 Regiment in northern Manas County.

Seasonal Variations in Groundwater Quality under Different Impacts Using Statistical Approaches

The objective of this study was to evaluate seasonal fluctuations in groundwater quality, determine the effects of different stressors on this resource, and recognize the potential pollution sources in a coastal region of southern Vietnam. Eleven samples collected in Ben Tre province during the dry and wet seasons were then analyzed for sixteen parameters, including pH, total dissolved solids (TDS), salinity, total hardness (TH), ammonium (NH₄⁺-N), nitrite (NO₂ˉ-N), nitrate (NO₃ˉ-N), sulfate (SO₄²ˉ), chloride (Clˉ), iron (Fe), manganese (Mn), lead (Pb), mercury (Hg), arsenic (As), coliforms, and Escherichia coli (E. coli). Pearson correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were employed. The results indicated that total dissolved solids, salinity, total hardness, Clˉ, E. coli and coliform were detected as contaminants in groundwater samples. The trend of fluctuations in the parameters was mostly higher in the dry season. Which Mn and coliform significantly fluctuated between the dry and wet seasons. Activities in industrial-craft areas, landfills and seawater-intruded areas negatively impacted groundwater quality, typically TDS in industrial-craft areas, coliform and E.coliat the landfill area. Six principal components obtained from PCA could explain 93.6% of the variance, and all parameters are responsible for variations in groundwater quality. Geology, discharged wastewater, landfill leachate, agricultural activities, and saltwater intrusion can be considered representative factors. CA grouped the collected samples into four clusters based on the similarity in water properties. The analysis results showed that the locations in each cluster have outstanding water quality characteristics, clusters I and III have high TDS characteristics, cluster II has coliforms, and cluster IV sets of locations with high salinity. This study is promised to partially fill the gap in comprehensive information on groundwater quality in the coastal province so that policymakers can develop sustainable water management strategies in the future. Doi: 10.28991/CEJ-2023-09-03-01 Full Text: PDF

Assessment of Groundwater Quality using Water Quality Index, and Geo-Spatial Tools

Groundwater is considered a significant component of valuable freshwater resources for the living beings living in the arid and semi-arid regions of Pakistan, factors such as climate change, landfill deposits, application of fertilizers and pesticides on agricultural lands, leakages from septic tanks, industrial effluents, and urbanization jeopardizing the groundwater quality that makes its timely assessment necessary for human survival to protect people from water-borne diseases. This research study was carried out to analyze the 13 physicochemical parameters in the 38 groundwater samples that were taken from nearby different locations of Akram, Pinyari, and Phuleli canal within the jurisdiction of district Hyderabad. 26 samples were taken from hand pumps, electric motors and 12 samples were taken from tube wells to investigate the variability in groundwater quality. The water quality index and kelly’s ratio, magnesium hazard, residual sodium carbonate, sodium absorption ratio, soluble sodium percentage, and permeability index were used to assess the suitability of groundwater for drinking, and agricultural purposes. The result of the study revealed that alkalinity, bicarbonates, carbonates, magnesium, PH, potassium, and sodium were within the permissible limit of WHO Standards in all the samples, while the concentration of calcium was crossing the permissible limit only in one sample. Moreover, the availability of Chloride (Cl) was found in 16 samples that were above the limit ranges from 274.9 to 2549, High concentration of EC was found in 14 samples than the permissible limit having values from 2212 to 8360 (P26), and Total Hardness (TH) were found only in 6 samples slightly high from the permissible limit ranges from 509 to 651, and TDS were present in excessive amounts than the allowable limit from 1100 to 4180 mg/l (P26) in 10 samples. Considering the Water Quality Index (WQI) it was observed that 8 sample falls in the good category, 2 samples in the poor category, 11 samples in the very poor category, and 17 samples in the unsuitable category of water quality.

Spatial evaluation of groundwater quality using factor analysis and geostatistical Kriging algorithm: a case study of Ibadan Metropolis, Nigeria

Abstract Necessity calls for the environmental aspects of groundwater to be evaluated and properly managed based on the observed spatial distribution with respect to quality, as it contributes to a significant portion of average water usage globally. Variations in groundwater quality in the Ibadan Metropolis might be a result of physical and chemical trends in the region leading to a decline in quality. The study was geared towards the spatial evaluation of groundwater quality using factor analysis and the Kriging algorithm. The parameters examined include pH, electrical conductivity, total dissolved solids, carbonates, chloride, nitrate, sulphate, calcium, sodium, magnesium, and potassium, which were sampled and analysed from the existing municipal deep wells in the Ibadan Metropolitan area; and distribution maps of each parameter were created using a geostatistical approach. Factor analysis examined the relationship between human activities and concentration levels. Semi-variograms were tested to ascertain the best-fitted model accuracy measures, average standard error, root mean square error, and root mean square error standardised. The groundwater index was calculated to ascertain the drinkability of the water in the study area. Overall, the result shows that the groundwater in the study area is suitable for consumption; drinking, and other uses. Kriging is a suitable assessment tool for modelling environmental parameters.

Appraisal of groundwater quality variation in the rural–urban division: a case study of Barrackpore sub-division, West Bengal

Appraisal of groundwater quality variation in the rural–urban division: a case study of Barrackpore sub-division, West Bengal

Spatiotemporal Variation of Groundwater Quality in North Central Province, Sri Lanka

Spatiotemporal Variation of Groundwater Quality in North Central Province, Sri Lanka

Use of the water quality index and multivariate analysis to assess groundwater quality for drinking purpose in Ratnapura district, Sri Lanka

Groundwater is a key source of freshwater for communities in many nations, including Sri Lanka. However, with the current trends of population growth and climate change, stress on groundwater is increasing at an alarming rate. Groundwater quality in Sri Lanka has already been depleted over time as a result of both anthropogenic and natural factors, and there is a significant likelihood that such issues will get worse in the near future. The overall groundwater quality in Ratnapura district has not been the subject of any prior studies, despite the fact that many residents depend on groundwater as their primary source of water. Under these circumstances, this groundwater quality study was conducted to assess the groundwater quality in Ratnapura district with respect to the drinking water quality standards. In this study, available data on 10 water quality parameters from 50 groundwater sources was utilized to analyze the groundwater quality using several statistical and graphical methods. In particular, the Water Quality Index (WQI), geostatistical modeling, Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), and spatial autocorrelation analysis were used to assess the overall water quality and potential causes for variations over the area. Overall results revealed significant deterioration of groundwater quality in the eastern and south-eastern areas of the district. Multivariate analysis results revealed substantial differences between groundwater in the wet zone and the dry zone of the district, implying increased mineralization of groundwater in the dry zone. Furthermore, the results demonstrate that both climate and soil properties have a substantial impact on groundwater quality variation across the district. Future hydrogeological research in the area, as well as water engineers, policy makers, government officials, donor agencies, etc., will benefit from the findings of this study.

CONCENTRATION LEVELS OF PHYSICO-CHEMICAL PROFILES AND QUALITY ASSESSMENT OF GROUNDWATER: A CASE STUDY OF SOUTHERN IJAW, BAYELSA STATE, SOUTHERN NIGERIA

This study examined the concentration levels of physico-chemical profiles of groundwater quality of communities in Southern Ijaw Local Government Area of Bayelsa State, Nigeria. The seasonal variation of groundwater quality were evaluated. Fifteen (15) communities within the LGA were selected and groundwater from hand-dug well (HDW-15samples) and borehole (BH-15samples) was sourced during the wet season (July) and dry season (March) and analyzed for seasonal variations. The difference in the mean of the parameters investigated during the dry and wet season revealed the difference in concentration level as influenced by the season attributes. The HDW showed a very strong correlation in wet and dry season physicochemical properties as well as no significant difference in the physicochemical properties of groundwater at both seasons. Also, the results of borehole water sample showed a very strong correlation in wet and dry season physic-chemical properties with no significant difference in the physicochemical properties of water at both seasons. There are similarities in various natural and anthropogenic activities influencing the concentrations during both wet and dry seasons. The mean values of parameters such as pH, TDS, TSS, Bicarbonate, Cl, SO34, NO2, Ca, Mg, K and P are within the permissible limit of WHO and NSDWQ during both seasons except TC.

Application of machine learning algorithms in the investigation of groundwater quality parameters over YSR district, India

Human life sustained for decades due to the availability of basic needs, and freshwater is one of them. However, groundwater quality is constantly under pressure. This can be attributed to anthropogenic activities not limited to urban areas but to rural zones. Machine learning methods like linear discriminant analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbour (KNN), Support Vector Machines (SVM) and, Random Forest (RF) models were used to analyse groundwater quality variables. The mean accuracy of each classifier was calculated, and the obtained mean accuracies were 77.5% (LDA), 87% (CART), 96% (KNN), 93.5% (SVM) and 96% (RF). RF and KNN models were selected as optimal models with higher accuracy. This study made it apparent that machine learning algorithms can estimate and predict water quality variables with significant accuracy. In this study, the observations and variables were compared with the water quality index and drinking water limits provided by the Bureau of Indian Standards. The water quality index for each observation was calculated. If at least four variables have a higher value than prescribed limits, it was assigned a value of 1; if more than four variables reported higher values, it was assigned a value of 2.

Assessment of seasonal groundwater quality variation employing GIS and statistical approaches in Kabul basin, Afghanistan

Assessment of seasonal groundwater quality variation employing GIS and statistical approaches in Kabul basin, Afghanistan