Assessment Of Groundwater Quality Research Articles

Assessing the Suitability of CCME WQI as a Groundwater Quality Monitoring Tool: An Environmental Ergonomics Case Analysis

This study was conducted with the aim of protecting groundwater, which plays a crucial role in ensuring food quality in the market, preserving public health, and safeguarding the ecosystem, as many regions rely on clean natural groundwater for their population’s survival. The objective of this study was to use the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for groundwater at 12 stations in the Okhla Industrial Area, Nangloi, and Karol Bagh in the Delhi Region. CCME WQI is an effective tool for assessing groundwater quality and communicating water conditions to various users. The research methodology involved fieldwork from June to October 2020 for three different periods in the year: pre-monsoon, monsoon, and post-monsoon, to observe variations in water quality and differences in various physicochemical properties of water. The CCME WQI was applied using sixteen water quality parameters, fourteen of which were physicochemical parameters and two of which were microbiological parameters. Among the physicochemical parameters were color, odor, pH, turbidity, nitrate, total hardness, iron, chloride, fluoride, total dissolved solids, calcium, magnesium, sulfate, and alkalinity, while the microbiological parameters included the total coliform and Escherichia coli counts. Based on the results obtained from the water quality index, station A9 scored between 0 and 44, indicating the lowest water quality index due to wastewater discharges and industrial contamination. The water quality at other stations also requires attention to achieve excellent ratings. The study concludes that serious measures should be taken for proper management of the area to protect the population from hazardous diseases. The research results show that stations 1, 2, and 10 were rated as excellent, station 12 as good, stations 4, 5, and 8 as moderate, stations 3, 6, and 11 as marginal, and station 9 as the poorest in terms of water quality in the year 2020 during the pre-monsoon, monsoon, and post-monsoon periods. To improve the parameters and groundwater quality, it would be necessary to reduce the impact of industry, anthropogenic–geogenic activities, and domestic activities.

Machine learning models for predicting water quality index: optimization and performance analysis for El Moghra, Egypt

ABSTRACT Assessing groundwater quality is vital for irrigation, but financial constraints in developing countries often result in infrequent sampling. This study comprehensively analyzes the groundwater quality of the El Moghra aquifer in Egypt's arid Western Desert, for its suitability for irrigation uses. Detailed hydrochemical analysis and advanced machine learning (ML) techniques, including geographic information systems, were employed to enhance spatial analysis and predictive accuracy. Various ML models, such as random forest, adaptive boosting, and extreme gradient boosting (XGBoost), were optimized using Bayesian optimization to predict the irrigation water quality index (IWQI) accurately. The evaluation incorporated visual and quantitative methods, alongside ranking analysis, to validate model effectiveness. Shapley Additive exPlanations feature importance analysis and a graphical user interface (GUI) model were developed based on the best predictive model. The results indicated that the groundwater quality is generally suitable for irrigation, with XGBoost showing the best performance, achieving a root mean square error of 5.602 and a determination coefficient (R²) of 0.872. Sodium concentration was identified as the most significant factor affecting the IWQI. The GUI facilitates easy prediction of IWQI, aiding agricultural water management and resource allocation within the region.

The Potential of Big Data and Machine Learning for Ground Water Quality Assessment and Prediction

The Potential of Big Data and Machine Learning for Ground Water Quality Assessment and Prediction

Groundwater Quality Assessment at East El Minia Middle Eocene Carbonate Aquifer: Water Quality Index (WQI) and Health Risk Assessment (HRA)

Around the world, groundwater supply is critical for vital needs such as drinking and irrigation. This work investigates groundwater in the carbonate aquifer of the Middle Miocene in the east El Minia area, Egypt. In this regard, thirty-two groundwater samples were collected. The water samples were analyzed for Ca2+, Mg2+, Na+, K+, Cl−, SO42−, NO3−, CO2−, HCO3−, Fe, Mn, Cd, As, Cr, Cu, and Pb. Groundwater has been evaluated using two methods, which are water quality index (WQI) and health risk assessment (HRA). The predominant groundwater is soft water, and the samples range in salinity from fresh to slightly salty. The groundwater mostly falls into the alkaline water type. All the groundwater samples under study are deemed low quality for human consumption due to water contamination. Fe, Mn, Cd, Cu, and Pb have high HQnc values, which can result in non-carcinogenic health issues in adults, while Mn, Cu, and Pb can give rise to non-carcinogenic health issues in children.

Assessment of groundwater quality and health risks in Ketama region (intrarif), Morocco

For many reasons, water from wells and natural springs is still widely used in Morocco. 90 groundwater samples were analyzed to assess the health risks associated with its quality in the Ketama region, including physicochemical analyses such as pH, electrical conductivity, total dissolved solids, bicarbonates, and nitrates using standardized methods, as well as bacteriological analyses covering total coliforms, fecal coliforms, Escherichia coli and fecal streptococci utilizing the membrane filtration method. Assessment of groundwater physicochemical quality showed that 13.41% of samples had nitrate concentrations exceeding the maximum value set by the World Health Organization (45 mg/ L). In comparison, 12.16% of samples were slightly acidic (pH < 6.5). Bacteriological analyses of the groundwater showed that the water points studied are contaminated with total coliforms, faecal coliforms, Escherichia coli, and faecal streptococci at rates of 80%, 50%, 35%, and 36%, respectively. In conclusion, groundwater in the Ketama region presented potential risks for users, particularly regarding waterborne diseases.

Unveiling the Dynamics and Sustainability of the Nubian Aquifer System in El-Marashda, Egypt Through Geophysical, and Hydrogeochemical Investigations

AbstractThis research investigates the geophysical, hydrogeochemical, and geological characteristics of the Nubian Aquifer System in the El-Marashda area, located beneath the Eastern Sahara Desert in northeastern Africa. The primary objective is identifying the aquifer geometry, assessing groundwater quality, and evaluating environmental pollution levels. A Magnetotelluric survey was employed to examine the subsurface geological composition and electrical resistivity characteristics of the aquifer system. The study revealed a freshwater-saturated Nubian Sandstone layer at depths between 986 and 1009 m with resistivity values of 101 to 182 Ohm.m, indicating a substantial and potentially sustainable groundwater resource. Overlying limestone and Marly Limestone layers influence the aquifer’s permeability and storage capacity. The chemical analysis of water from three wells showed suitability for drinking and irrigation, with no sodium and magnesium levels hazards. The Heavy Metal Pollution Index (HPI) and Heavy Metal Evaluation Index (HEI) indicated low to medium contamination, posing potential environmental health risks. Human health risk assessments using USEPA methodology found acceptable non-carcinogenic risks, with Hazard Quotients (HQs) for heavy metals below 1 and a negligible Hazard Index (HI). The comprehensive investigation underscores the potential for sustainable groundwater utilization in El-Marashda. It highlights the aquifer’s suitability for irrigation, with low contamination levels and minimal health risks. These findings provide a foundation for informed and sustainable water resource management, environmental protection, and resilient infrastructure development in the region. The methodologies and results align with global standards, demonstrating their applicability in globally diverse geological contexts. This research contributes valuable baseline data for future studies and monitoring efforts, whether at local or global sites, emphasizing the importance of continued investigation to ensure sustainable groundwater management.

Empowering Navajo Nation's Water Quality Monitoring through State-of-the-Art Paper-Electrochemical Sensors

The NSF-PREM research collaborative effort between Navajo Technical University (NTU) and Harvard University aims to address the critical issue of water contamination within the Navajo Nation. Decades of uranium mining and mineral extraction have left a lasting mark on the Navajo land and groundwater resources, necessitating effective solutions. The Nano-electrochemical Analysis and Energy Storage Laboratory (NEST LAB) at NTU has developed flexible paper-based sensors integrated with advanced electrochemical techniques to detect heavy metal concentrations in water samples. These sensors are cost-effective, easy to fabricate, and highly reliable, offering real-time monitoring capabilities. The projects core goal is to expedite water quality analysis and empower the Navajo community to detect potential contamination promptly. By distributing these sensors to local chapter houses, residents can independently assess groundwater quality, fostering a sense of ownership and proactive environmental stewardship. This partnership exemplifies the power of community-driven solutions and trains Navajo students to get involved in scientific innovation to safeguard the environment for future generations in the Navajo Nation.

Groundwater quality assessment for drinking, irrigation purposes and fuzzy logic-based water quality index for industrial suitability in Walajapet taluk, Ranipet district, Tamil Nadu, India

ABSTRACT Ranipet district in Tamil Nadu is one of the major industrial zones in India. Groundwater has been extensively used in this region for drinking, agricultural, and industrial purposes. For finding the groundwater quality, representative samples have been collected in the premonsoon (PRM) and postmonsoon (POM) seasons of 2023 and analysed for major physicochemical parameters. The drinking suitability was analysed based on drinking water quality index, and it showed that 68.52 and 70.37% of samples from the PRM and POM seasons are classified as poor groundwater for drinking. The groundwater's suitability for irrigation was analysed based on various irrigation quality indices, and it highlighted that most of the groundwater was suitable for agriculture. Industrial suitability was determined by several industrial quality indices. Due to the simultaneous application of several indices, a sample is categorised into many water quality groups, introducing bias into handling and decision-making. The Mamdani fuzzy inference system creates a unique integrated industrial water quality index to address this issue. The index revealed that only 24.07 and 9.26% of samples from the PRM and POM seasons, respectively, were free of corrosion or scaling, while the remaining samples were inappropriate for industrial use.

Assessment of Groundwater Quality of Hubballi City, Karnataka, India by Using Canadian Council of Ministers of the Environment Water Quality Index, Weighted Arithmetic Water Quality Index and Geospatial Techniques

Assessment of Groundwater Quality of Hubballi City, Karnataka, India by Using Canadian Council of Ministers of the Environment Water Quality Index, Weighted Arithmetic Water Quality Index and Geospatial Techniques

Groundwater Quality Assessment: A Case of Urban Population Demography and Nutrient Enrichment in Ibadan, Southwestern Nigeria

Groundwater Quality Assessment: A Case of Urban Population Demography and Nutrient Enrichment in Ibadan, Southwestern Nigeria

Assessment of groundwater quality for irrigation purpose in Yadadri Bhuvanagiri district, Telangana

Assessment of groundwater quality for irrigation purpose in Yadadri Bhuvanagiri district, Telangana

Assessment of groundwater quality and suitability for irrigation purpose using irrigation indices, remote sensing and GIS approach

Assessing both the quantitative and qualitative aspects of groundwater is essential for evaluating its suitability for irrigation and drinking purpose. Consequently, this current study showcases its importance by determining groundwater quality in Sundargarh district of, India, where groundwater serves as vital water resources. 360 groundwater samples were collected from various dug wells during pre-monsoon season of 2014–21 and analyzed for major ions, some important irrigation water quality indices along with pH, EC and TDS. Statistical evaluation of groundwater quality parameters was performed by physiochemical analysis with association of ArcGIS 10.4 for developing the spatial mapping. Furthermore, statistical and hydrochemical analysis was executed by exhibiting box plot generation, correlation study and hierarchical cluster analysis followed by categorization of water facies in , 1920; CGWB, 2013; Gad and Hattab, 2019’ has/have not been found in the reference list. Please add the corresponding reference(s) to the reference list.>Xlstat 2023, SPSS 23 and Diagrammes 6.1. Groundwater is mostly characterized as Na+-SO42- and deep meteoric percolation (DMP) type based on Base Exchange Indices with the dominance of Ca2+ and HCO3− as the major cation and anion respectively. Besides that, groundwater from 92%, 96%, 84%, 100%, 99%, 98%, 57%, 64%, 100%, 77%, 98% and 89% dug wells are found to be highly suitable for cultivation of major crops of this district depending on spatial variation of EC, TDS. Cl−, SAR, RSC, KR, PI, %Na, ESP, MAR, SSP and PS respectively. Groundwater facies are mostly categorized as Ca–HCO3 (60.8%) and C2–S1 (65.5%) type based on Piper and Wilcox diagram respectively. The dominant geochemical controlling factors are evaporation, reverse ion exchange and silicate weathering. Therefore, the objectives of this present research may provide necessary information to the regulatory boards and policy makers for efficient monitoring of groundwater quality and contaminated aquifers in Sundargarh district to make fit this crucial water resources for agricultural purpose.

Spatial assessment of groundwater quality in Panteka Market Tudun Nupawa, Kaduna, Nigeria

Spatial assessment of groundwater quality in Panteka Market Tudun Nupawa, Kaduna, Nigeria

Investigating seawater intrusion and salinization using the integration of hydrochemical and geoelectrical techniques

Seawater intrusion poses a significant environmental threat to water resources, agriculture, and ecosystems. We investigate the extent of seawater intrusion and salinization in the eastern coastal aquifers of Saudi Arabia. Hydrochemical measurements and electrical resistivity tomography (ERT) techniques are used to assess groundwater quality and the subsurface extension of seawater intrusion. Two resistivity profiles, 475 m long each, are analyzed to gain insights into the subsurface geology and seawater intrusion. The inversion of the recorded resistivity data reveal four distinct subsurface layers. The uppermost layer consists of surficial deposits, followed by a sandy seawater intrusion layer, beneath which lies a marl layer, and at the bottom, a dolomitic limestone layer representing the brackish-water aquifer. The ERT results are integrated with hydrochemical and hydrogeologic results from 12 wells to overcome the limitations of the ERT. The findings of this study would facilitate the development of efficient mitigation strategies and sustainable management of the groundwater resources in the study area or similar coastal regions affected by seawater intrusion. Understanding and delineating the boundary between saline and fresh water is crucial for safeguarding water resources for agricultural purposes, preserving ecosystem health, and ensuring the long-term sustainability of water supplies in coastal areas.

Assessment of Groundwater Quality of Different Districts in Odisha for Agricultural and Drinking Purposes

Assessment of Groundwater Quality of Different Districts in Odisha for Agricultural and Drinking Purposes

Investigation of Heavy Metal Composition and Associated Health Risks from Selected Groundwater Wells in Temeke, Dar-es-Salaam

Water quality continues to be the challenge to residents in Dar es Salaam due to various anthropogenic activities in the city. This study was conducted to assess groundwater quality by determining concentrations of heavy metals. Both probability and Nonprobability sampling techniques were used to collect samples from 40 groundwater wells in 24 wards of Temeke municipal and analysed using Microwave Plasma Atomic Emission Spectrometer (Agilent 4210 MP-AES) at the Geochemistry Laboratory of the University of Dar es Salaam. Results indicated varying heavy metal concentrations ranging from 0.71 ± 0.08 to 6.64 ± 0.21 mg/l for As, 0.02 ± 0.01 to 0.07 ± 0.01 mg/l for Co and 0.16 ± 0.01 to 0.02 ± 0.01 mg/l for Pb. The As, Co and Pb concentrations exceeded (P &amp;lt; 0.05) the recommended TBS standards of 0.05 mg/l, 0.003 mg/l and 0.01 mg/l respectively. Other concentrations ranged from 0.01 ± 0.01 to 0.88 ± 0.01 mg/l for Cu, 0.02 ± 0.01 to 3.55 ± 0.02 mg/l for Fe, 0.00 ± 0.00 to 4.63 ± 0.03 mg/l for Mn and 0.01 ± 0.01 to 3.00 ± 0.01 mg/l for Zn. The Cu, Fe, Mn and Zn concentrations were below (P &amp;gt; 0.05) the allowable TBS limits of 0.05 mg/l, 0.3 mg/l, 0.1 mg/l and 3 mg/l respectively. Health risk analysis revealed potential adverse health effects from long term consumption of As, Mn and Pb with Hazard Quotient exceeding 1 (HQ &amp;gt; 1). The Hazard Index (HI) for all groundwater samples was also above 1 (HI &amp;gt; 1) indicating a higher likelihood of adverse health effects. The study concluded that groundwater wells in Temeke Municipal are affected through natural and anthropogenic activities leading to high levels of heavy metal concentrations. Also, this study provides valuable information on risk associated by continued usage of groundwater in Temeke region and hence informs respective stakeholders on groundwater quality and potential risks thereby emphasizing the need for remedial measures and stricter regulations to safeguard public health. The study recommends the need for regular groundwater quality and safety monitoring to assess the levels of heavy metals concentrations and implement sustainable groundwater management strategies to address the increasing water demand in Temeke municipal, Dar es Salaam.

Comprehensive assessment of groundwater quality in the Prayagraj District, Ganga Basin.

Urbanization has severely impacted the world water resources especially the shallow groundwater systems. There is a need of a robust method for quantifying the water quality degradation, which is still a challenge for most of the urban centers across the world. In this study, a highly urbanized region of Ganga basin is selected to critically evaluate commonly used WQIs and compare with fuzzy modeling. A total of 28 water samples were collected from diverse sources (surface and groundwaters) in the vicinity of urban region covering an area of 216 km2 during the premonsoon period. TDS, TH, NO3-, and F- values were found to be above the permissible limits in 57%, 89%, 4%, and 7% samples, respectively. The WQIs (entropy and integrated) outputs were found to be similar with 89% of the samples falling under moderate category. Fuzzy modeling was carried out allowing user-defined weighting factors for the most influential ions, and the output suggested 96% of the samples falling under moderate to excellent categories. Based on the chemical results and considering the lithology of the study area, the geochemical reactions controlling the water quality were deduced. This study outlines a systematic approach of evaluating the overall water quality of an urban region highlighting the merits and limitations ofWQIs. It also justifies the immediate need to generate more robust data to achieve the sustainable development goals 6 (clean water and sanitation) and 11 (sustainability of cities and human settlement).

Assessment of groundwater quality using water quality index, multivariate statistical analysis and machine learning techniques in the vicinity of an open dumping yard

Assessment of groundwater quality using water quality index, multivariate statistical analysis and machine learning techniques in the vicinity of an open dumping yard

Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region.

Water plays a significant role in sustaining the lives of humans and other living organisms. Groundwater quality analysis has become inevitable, because of increased contamination of water resources and global warming. This study used machine learning (ML) models to predict the water quality index (WQI) and water quality classification (WQC). Forty groundwater samples were collected near the Ranipet industrial corridor, and the hydrogeochemistry and heavy metal contamination were analyzed. WQC prediction employed random forest (RF), gradient boosting (GB), decision tree (DT), and K-nearest neighbor (KNN) models, and WQI prediction used extreme gradient boosting (XGBoost), support vector regressor (SVR), RF, and multi-layer perceptron (MLP) models. The grid search method is used to evaluate the ML model by F1 score, accuracy, recall, precision, and Matthews correlation coefficient (MCC) for WQC and the coefficient of determination (R2), mean absolute error (MAE), mean square error (MSE), and median absolute percentage error (MAPE) for WQI. The WQI results indicate that the groundwater quality of the study area is very poor and unsuitable for drinking or irrigation purposes. The performance metrics of the RF model excelled in predicting both WQC (accuracy = 97%) and WQI (R2 = 91.0%), outperforming other models and emphasizing ML's superiority in groundwater quality assessment. The findings suggest that ML models perform well and yield better accuracy than conventional techniques used in groundwater quality assessment studies.

Water Quality Assessment in an Area Degraded by Urban Solid Waste in Southern Brazil

ABSTRACTIn most Brazilian municipalities, urban solid waste (USW) is disposed of in open dumps, with numerous sites now being closed, monitored, and rehabilitated. One location, the “old dump” area in the Portão municipality (southern Brazil), previously served as an irregular repository for USW and industrial solid waste (ISW). Its use continued until 1993 when it was closed for a natural remediation process. For this reason, this study aimed to assess groundwater quality in the Portão “old dump,” employing physicochemical, microbiological, and toxicity quality indicators. The study's scope was extended to encompass the Portão Stream as well. Notably, the second collection campaign revealed elevated dissolved aluminum (Al3+), iron (Fe2+), and nitrate levels in all groundwater samples (from PZi wells, i = 1–6), with the PZ3 monitoring well experiencing the most pronounced impact. Further quality indicators, such as total phosphorus, thermotolerant coliforms, BOD5, as well as Al3+ and copper (Cu2+) levels in the second water collection campaign from Portão Stream, were classified as Class 4, suggesting that the water is suitable only for navigation and aesthetic purposes. Conductivity analysis identified Portão Stream as another impacted area. Moreover, during the second collection campaign, the study uncovered an escalation in micronuclei (MN) frequency and chromosomal alterations in PZ5. Downstream water samples from Portão Stream exhibited similarly heightened MN levels. This study's investigation into water quality is a concrete example of the implications of improper USW management. These findings underscore the pressing need for effective waste management strategies to mitigate environmental degradation and protect public health.