Groundwater Vulnerability Assessment Research Articles

Assessment of Groundwater Vulnerability to Seawater Intrusion Using GALDIT, SITE and SIVI Methods in Laspias River Coastal Aquifer System, NE Greece

This paper presents the investigation of groundwater vulnerability to seawater intrusion of the aquifer system in the coastal area of Laspias River, NE Greece, for the year 2023, by applying the GALDIT, SITE and SIVI methods, in the context of the groundwater management of the area. The relevant research works include the collection and analysis of data and information regarding the geological and geomorphological environment, as well as the hydrogeological system of the area. The calculation of the GALDIT, SITE and SIVI indices values is described, and the results from the application of the methods are presented, as well as the design of relevant groundwater vulnerability maps of the study area. This paper concludes with findings and proposals useful for the reliable assessment of the hydrogeological regime of the wider study area.

Framework development for the physical vulnerability assessment index of hand-dug Wells in Are-Ekiti, Southwestern Nigeria.

The article presents a comprehensive framework for assessing the physical vulnerability of hand-dug wells within the Are Community, Southwestern Nigeria. The study spans from March to April 2023 and meticulously examines 90 wells, focusing on critical parameters such as well collar, well cover, and well lining information. The analysis reveals significant variations in well collar construction materials and dimensions, emphasizing the community's adaptive strategies. The Well Collar Height Index (WCi), Well Cover Index (WCOi), Well Lining Index (WLi), and the derived Vulnerability Index categorize wells into vulnerability classes, offering a nuanced understanding of susceptibility levels. Notably, the study identifies wells with Very High vulnerability that demand urgent attention, as well as wells with effective protective measures categorized as Very Low vulnerability. The article emphasizes the need for a nuanced understanding of local practices and materials, highlighting the variability in well collar construction. It discusses the implications of well cover conditions and the critical role of well linings in assessing groundwater vulnerability. The Vulnerability Index combines these parameters, guiding targeted interventions based on risk severity. The study lays the groundwork for future interventions to enhance the safety and sustainability of water sources within the Are Community. It recommends immediate comprehensive measures for highly vulnerable wells, ongoing monitoring, community engagement, and knowledge sharing. The future scope includes incorporating geochemical analysis, targeted interventions, regular maintenance, community training, and exploring alternative water sources for sustainable improvements.

Groundwater vulnerability assessment of elevated heavy metal contamination related health hazard in coastal multi-aquifers of Sundarban Biosphere Reserve, India

The concept of groundwater (GW) vulnerability emerged as a response to the escalating contamination of GW globally. Over recent decades, both scholars and policymakers have extensively utilized GW vulnerability assessments to safeguard groundwater from pollution. Within the Sundarban Biosphere Reserve (SBR), inhabitants residing near coastal aquifers face significant challenges, notably the scarcity of fresh water during the hot and dry season. Furthermore, there is a concern regarding the presence of heavy metals (HMs) in this region, adversely impacting GW quality. In both Indian and global contexts, HM contamination, including arsenic (As), fluoride (F‾), and nitrate (NO3–), and its repercussions on human health (HH) in coastal districts, represent critical issues. In light of these challenges, this study aims to assess GW vulnerability and its implications for HH in SBR utilizing the Hazard Quotient (HQ) approach. Fifteen hydro-geochemical parameters have been selected for this research endeavor. Various statistical indices, such as “groundwater quality index (GWQI)”, “degree of contamination (CD)”, “index of ecological risk (ERI)”, and “human health hazard index (HHHI)”, have been employed to accomplish the study objectives. Piper's and Box plot diagrams were utilized to assess hydrogeochemical properties and GW quality. The findings reveal average concentrations of HMs, such as As, NO3–, and F‾ in the study area, to be 0.204 mg/l, 6.28 mg/l, and 0.79 mg/l, respectively. Among all variables, a positive correlation of 0.876 is observed between electrical conductivity (EC) and sodium ions (Na+). Eventually, the outcomes of this study can provide valuable insights for planners and policymakers to make informed decisions regarding the sustainable management of water resources.

Comprehensive quantitative determination of aquifer confinement based on tidal response of well water level and its application in North China

Aquifer confinement represents a pivotal property that significantly influences the vulnerability and contamination risk of groundwater resources. Several methods have been proposed for determining aquifer confinement by analyzing the response of well water level to Earth tides and atmospheric tides. In this study, we evaluated the performance of the existing single methods and put forward an optimized comprehensive approach. We compared the determination results of the three single methods with those of a comprehensive method using water-level data from 39 earthquake precursor monitoring wells in North China. The results demonstrate that the comprehensive method effectively determined aquifer confinement, significantly reducing the uncertainty associated with the three single methods. The application of the comprehensive method in North China reveals that aquifer confinement may undergo temporal variations during long-term continuous observation, especially in areas where the confining properties of aquifers may vary due to human activities and earthquakes. In such areas, the comprehensive method facilitates accurate assessment of groundwater vulnerability, as well as the potential dispersion of underground pollutants.

Spatio-temporal prediction of groundwater vulnerability based on CNN-LSTM model with self-attention mechanism: A case study in Hetao Plain, northern China

Located in northern China, the Hetao Plain is an important agro-economic zone and population centre. The deterioration of local groundwater quality has had a serious impact on human health and economic development. Nowadays, the groundwater vulnerability assessment (GVA) has become an essential task to identify the current status and development trend of groundwater quality. In this study, the Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models are integrated to realize the spatio-temporal prediction of regional groundwater vulnerability by introducing the Self-attention mechanism. The study firstly builds the CNN-LSTM model with self-attention (SA) mechanism and evaluates the prediction accuracy of the model for groundwater vulnerability compared to other common machine learning models such as Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The results indicate that the CNN-LSTM model outperforms these models, demonstrating its significance in groundwater vulnerability assessment. It can be posited that the predictions indicate an increased risk of groundwater vulnerability in the study area over the coming years. This increase can be attributed to the synergistic impact of global climate anomalies and intensified local human activities. Moreover, the overall groundwater vulnerability risk in the entire region has increased, evident from both the notably high value and standard deviation. This suggests that the spatial variability of groundwater vulnerability in the area is expected to expand in the future due to the sustained progression of climate change and human activities. The model can be optimized for diverse applications across regional environmental assessment, pollution prediction, and risk statistics. This study holds particular significance for ecological protection and groundwater resource management.

Application of the fuzzy analytic hierarchy process for water resources in the Wadi AlHasa catchment, Jordan

This article introduces a groundwater vulnerability assessment model that utilises the fuzzy analytic hierarchy process (FAHP) in the Wadi AlHasa catchment, Jordan. The assessment takes into account both geomorphological and hydrogeological variables, employing a comprehensive methodology that integrates various parameters. To evaluate the catchment, the study employs remote sensing and Geographic Information System (GIS) techniques. The analysis of the digital elevation model enables the creation of a map illustrating the diverse geomorphology of the catchment. This geomorphology significantly influences drainage density, direction, and the spatial distribution and intensity of flash flood events. Moreover, the study develops and maps a fuzzy FAHP DRASTIC vulnerability index, which proves to be a valuable tool for assessing the susceptibility of groundwater resources to contamination. The unique feature of the index is its ability to incorporate uncertain or subjective data, providing a means to evaluate the significance of various influencing factors. This information serves as critical support for decision-making and management efforts geared towards safeguarding and enhancing groundwater resources. Within the study area, the DRASTIC vulnerability index values span from 0.08325 to 0.28409, with 18% of the site exhibiting a high vulnerability rate. Additionally, the article implements a managed aquifer recharge model (MAR), with 31% of the area falling into MAR classes. Among these, 22.1% are classified as a high MAR class, while 0.7% belong to a very high MAR class. These findings underscore the feasibility of MAR projects in regions with limited water resources.

Advancing groundwater vulnerability assessment in Bangladesh: a comprehensive machine learning approach

In response to Bangladesh's severe water shortages, this research delves into the intricate dynamics of groundwater vulnerability. Integrating often-overlooked factors such as topography, meteorology, socio-economic conditions, and land use & geology, the study employs advanced Random Forest (RF) modeling. Rigorously analyzing 200 strategically chosen sample points, the research uncovers critical areas like Rajshahi, Nawabganj, Naogaon, and Dhaka, constituting 21% of the land, as highly vulnerable. In contrast, regions like Rangpur, Mymensingh, and Barisal, encompassing 31% of the area, exhibit lower vulnerability. Topographic factors, accounting for 45% of the vulnerability, including aspect, drainage density, and slope, significantly influence susceptibility. Socio-economic elements contribute 22%, particularly population density and industrial activities. The RF model achieves exceptional accuracy (over 90%), emphasizing the complexity of groundwater dynamics. By integrating geological, social, and economic aspects, the study provides actionable insights for nuanced and sustainable management strategies. This research not only unveils a highly accurate groundwater vulnerability map, enriching scientific understanding, but also offers a unique approach by incorporating often-overlooked variables and leveraging machine learning. These insights empower policymakers and urban planners to craft targeted and sustainable groundwater management strategies, ensuring a resilient water supply system for Bangladesh's growing population. Through this work, the aim is to significantly contribute to the scientific community while providing data-driven solutions for the nation's pressing water challenges.

Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq

Groundwater vulnerability assessment using a GIS-based DRASTIC method in the Erbil Dumpsite area (Kani Qirzhala), Central Erbil Basin, North Iraq

Evaluating arsenic contamination in northwestern Bangladesh: A GIS-Based assessment of groundwater vulnerability and human health impacts

One of the biggest environmental worries in the world today is the risk of arsenic (As) contamination in groundwater. The Atomic Absorption Spectrometer (AAS) was used in this work to assess the As content in groundwater samples from 38 shallow (27 m) tubewells in northwest Bangladesh to determine the existing situation, potential source(s), and likely health risk of As and other important water quality parameters. The range of arsenic concentrations (μgL−1) was troublesome and greater than the WHO recommended level for drinking water, ranging from 0.50 to 164 (mean ± SD: 20.22 ± 36.46). In groundwater, the concentrations of Fe, and Mn vary from 0.04 to 52.75 mgL−1 (mean ± SD: 4.23 ± 9.68), and 0.23 to 3.27 mgL−1 (mean ± SD: 1.10 ± 0.67). The obtained groundwater samples have pH values ranging from 5.9 to 7.1, which indicates a somewhat acidic to neutral character. Major cations have an average abundance that is as follows: Ca2+ > Mg2+ > Na+ > K+, while major anions have an average abundance that is as follows: HCO3− > Cl− > SO42− > NO3−; Ca2+ and HCO3− are the main cation and anion, respectively. The groundwater in the Rajarampur village was deemed unfit for drinking or irrigation based on analyses of water quality performed using the entropy water quality index. The Ca–HCO3 type of water, in which Ca2+ and HCO3− are the main positive ions and negative ions, is suggested by the Piper tri-linear diagram. It was discovered that silicate weathering regulates the hydro-geochemical activities in groundwater using a bi-variate examination of several hydro-chemical variables. Four major clusters were observed for the water sample. According to reductive dissolution processes and principal component analysis, the arsenic in groundwater is geogenic in origin. Arsenic is discharged from sediment to groundwater by reductive dissolution of FeOOH and MnOOH, as shown by the modest connection between As, Fe, and Mn. The United Nations Environmental Protection Agency's (USEPA) suggested value for probable cancer risk assessment was 10−6, however the probable cancer risk assessment found a higher value, indicating that the population in the study region was at high risk for cancer. Remedial measures for arsenic mitigation include removing arsenic from groundwater after it is extracted, searching for alternative aquifers, and implementing various water-supply technologies such as dugwells, deep tubewells, pond-sand filters, and rainwater harvesting systems.

Geo-electric assessment of groundwater potentials and vulnerability to contaminants for sustainable water management at Utue-Ogume, Delta State, Nigeria

he study focuses on assessing groundwater potentials and the effectiveness of the overburden protective layer in preventing contaminant intrusion into the groundwater aquifer within a municipality in the Western Niger Delta. Aim. Employing Vertical Electrical Sounding (VES), 2-D resistivity imaging, and Dar-zarrouk parameters, the research aims to investigate the geoelectric characteristics of the subsurface layers, delineate the aquiferous layer, and assess the protective capacity of the overburden. Methods. Nine VES were conducted using the Mini-Res Resistivity Meter with the Schlumberger array. Data processing utilized IPI2win software, revealing seven to eight geoelectric layers. The aquiferous layer, situated between the fifth and sixth layers, exhibited varying resistivity (924.9Ωm to 1629Ωm), thickness (34.52 m to 79.20 m), and depth (55.95 m to 106.00 m). Results. Dar-zarrouk hydraulic parameters (hydraulic conductivity, longitudinal conductance, transverse resistance, and transmissivity) were derived from aquifer resistivity and thickness. Hydraulic conductivity ranged from 6.55 m/day to 6.80m/day, transmissivity from 228.5 m²/day to 538.6 m²/day, longitudinal conductance from 0.031Ω⁻¹ to 0.076Ω⁻¹, and transverse resistance from 37385.1Ωm² to 129016.8Ωm². Zones with contrasting parameter values were identified. Conclusion. The overburden protective layer was rated as having poor capacity, rendering the aquifer highly vulnerable to contaminants. Conversely, the aquifer demonstrated potential for providing portable water, reflecting subsurface heterogeneity and ample hydraulic pressure. A recommended hydrochemical study will further assess water portability. Актуальность работы. Исследование посвящено оценке потенциала подземных вод и эффективности водоупорного слоя вскрышных пород в предотвращении проникновения загрязняющих веществ в водоносный горизонт подземных вод на территории муниципалитета в дельте Западного Нигера. Цель. Вертикальное электрическое зондирование (ВЭЗ), двухмерная резиститивная визуализация и параметры Дар-Заррук использовались для исследования потенциала грунтовых вод и прочности пород водоупорного слоя. Методы. Девять профилей ВЭЗ были исследованы с использованием измерителя сопротивления Mini-Res установкой Schlumberger. Данные ВЭЗ были обработаны с помощью программного обеспечения IPI2win, которое оконтурило от семи до восьми геоэлектрических слоев. Водоносный горизонт, расположенный между пятым и шестым слоями, показал вариацию сопротивления от 924,9 Ωm до 1629 Ωm, мощность от 34,52 до 79,20 м и глубину от 55,95 до 106,00 м. Результаты. Гидравлические параметры Дар-Заррука (гидравлическая проводимость, продольная проводимость, поперечное сопротивление и пропускающая способность) были получены на основе удельного сопротивления и мощности водоносного горизонта. Гидравлическая проводимость варьировалась от 6,55 м/день до 6,80 м/день, пропускающая способность – от 228,5 м2/день до 538,6 м2/день, продольная проводимость – от 0,031 Ом⁻1 до 0,076 Ом⁻1 и поперечное сопротивление – от 37385,1 Ом∙м2 до 129016,8 Ом∙м2. Выявлены зоны с контрастными значениями параметров. Заключение. Защитные свойства водоупорного горизонта были оценены как низкие, что делает водоносный горизонт очень уязвимым для загрязнений. И наоборот, водоносный горизонт продемонстрировал потенциал для обеспечения питьевой водой, что отражает неоднородность недр и достаточное гидравлическое давление. Рекомендуемое гидрохимическое исследование позволит дополнительно оценить возможность переноса веществ воды.

Z-number based assessment of groundwater vulnerability to seawater intrusion

Groundwater (GW) quality assessment is an essential issue, especially in arid and semi-arid regions, due to its critical role in obtaining requirements for freshwater. The GALDIT method is widely recognized as a practical approach for assessing GW susceptibility, which considers six key factors, including the occurrence of groundwater (G), hydraulic conductivity of the aquifer (A), elevation of groundwater above sea level (L), distance from the shoreline (D), impact of existing seawater intrusion (I), and thickness of the aquifer (T). The GALDIT method, being an unsupervised model, has a drawback in that it depends on expert opinion for parameter ranking, leading to an increase in uncertainty. To address this uncertainty and evaluate the susceptibility of the aquifers of Urmia lake basin to saltwater intrusion, this study employed the Z-number which is a novel adaptation of Fuzzy Logic (FL). In contrast to classic FL that does not account for data reliability, the Z-number approach considers both constraints and data reliability, making it a more effective method to manage data uncertainty compared to classic fuzzy models. To illustrate this methodology, the GALDIT parameters (inputs) and Electrical Conductivity (EC) values (outputs) were employed to determine the vulnerability of aquifers. Additionally, the GALDIT method was utilized as a benchmark model to evaluate the inherent vulnerability of aquifers, and its outcomes were compared with those of the proposed model. Upon analyzing the results, it was found that the Z-number Based Modeling (ZBM) not only outperformed the GALDIT method but also enhanced the quality of outcomes by 85% and 35% based on Heidke Skill Score (HSS) and Total Accuracy (TA) criteria compared to the classic FL.

Enhancing groundwater vulnerability assessment for improved environmental management: addressing a critical environmental concern

Groundwater serves as a primary water source for various purposes. Therefore, aquifer pollution poses a critical threat to human health and the environment. Identifying the aquifer’s highly vulnerable areas to pollution is necessary to implement appropriate remedial measures, thus ensuring groundwater sustainability. This paper aims to enhance groundwater vulnerability assessment (GWVA) to manage aquifer quality effectively. The study focuses on the El Orjane Aquifer in the Moulouya basin, Morocco, which is facing significant degradation due to olive mill wastewater. Groundwater vulnerability maps (GVMs) were generated using the DRASTIC, Pesticide DRASTIC, SINTACS, and SI methods. To assess the effectiveness of the proposed improvements, 24 piezometers were installed to measure nitrate concentrations, a common indicator of groundwater contamination. This study aimed to enhance GWVA by incorporating new layers, such as land use, and adjusting parameter rates based on a comprehensive sensitivity analysis. The results demonstrate a significant increase in Pearson correlation values (PCV) between the produced GVMs and measured nitrate concentrations. For instance, the PCV for the DRASTIC method improved from 0.42 to 0.75 after adding the land use layer and adjusting parameter rates using the Wilcoxon method. These findings offer valuable insights for accurately assessing groundwater vulnerability in areas with similar hazards and hydrological conditions, particularly in semi-arid and arid regions. They contribute to improving groundwater and environmental management practices, ensuring the long-term sustainability of aquifers.

Assessing Groundwater Resources Vulnerability with the New DRASTIC-LP: A Case Study in Chiang Mai Province, Thailand

Groundwater vulnerability has gained widespread attention, particularly in Chiang Mai Province, one of Thailand’s fastest-growing cities, which is experiencing rapid development in both economic and social sectors. The expansion of urban communities and the industrial, tourism, and agriculture sectors has resulted in the overutilization of available resources, notably water resources. This overuse, coupled with the adoption of modern technology to boost productivity and meet market demands, has led to an increased reliance on groundwater to supplement surface water sources, providing benefits across all sectors. However, the economic and social growth plays a pivotal role in shaping the diversity of land use, encompassing residential, commercial, industrial, and agricultural activities. These activities, in turn, directly contribute to environmental pollution, particularly in terms of the risk of groundwater contamination in Chiang Mai Province. This study aims to predict the future vulnerabilities of groundwater resources under an ensemble of climate change scenarios and changes in land-use patterns. Chiang Mai Province in northern Thailand is one of the fastest-growing cities and therefore is experiencing rapid urbanization, as well as land-use pattern changes, which was important for the case study. The new DRASTIC model, namely the DRASTIC-LP model, combined with GIS-based techniques and overlay techniques, was used to generate the map of groundwater resource vulnerabilities. A point pollution source (P)-related land-use pattern (L) that represents contamination impacts was considered an additional new DRASTIC parameter. The study’s findings reveal the high reliability and maximum effectiveness of the new DRASTIC-LP model in assessing groundwater vulnerability and contamination-risk areas under a climate change scenario (by MIROC-ESM-CHEM model under RCP.8.5 scenario) and land-use pattern changes (by CA_Markov Chian Model) for both the current year (2020) and the next 50-year period (2021–2070). Furthermore, the new DRASTIC-LP model is employed to trace the movement of pollutants from high- to very high-risk areas based on the groundwater vulnerability and contamination-risk maps. The results highlight that waste disposal dumping sites pose a more critical distribution and movement of pollutants when compared to industrial sites. Additionally, unconsolidated aquifers and cracked consolidated rock aquifers show a potentially higher occurrence of pollutant distribution and movement when compared to consolidated aquifers. Consequently, the study’s outcomes are applied to formulate guidelines for the management and control of groundwater resource contamination. These guidelines serve as valuable tools for decision makers, aiding in pollution prevention and the effective management of contamination risks in groundwater resources.

Introducing reverse Multi Influencing Factor technique in DRASTIC model for groundwater vulnerability assessment

Effective groundwater resource management has become essential to the development of urbanized areas, particularly in regions with significant agricultural and industrial activity. In the present study, a multi-criteria decision-analysis techniques methodology was used to assess the groundwater vulnerability of Seonath basin. The objective of this study is to identify the areas that are more susceptible to groundwater contamination by incorporating various hydrogeological layers from DRASTIC into the geographical information system (GIS) platform. To enhance the weights of the DRASTIC parameters used for the identification of the groundwater vulnerability index values, apart from the application of the widely-used multiple influencing factors (MIF) method, a new modified MIF method (hereafter named RMIF) was also introduced and applied. Based on their index map, the final results were classified into five vulnerable classes: very low, low, moderate, high, and very high. Lower index values indicated areas that were less vulnerable, and vice versa. DRASTIC-RMIF is performing better than DRASTIC and DRASTIC-MIF, respectively majority of the total area lies in moderately vulnerable zones: 77.50 %, 70.52 % and 28.20 %. In order to validate the groundwater vulnerability zones, we also attempted to test and create a relationship between nitrate and the final groundwater vulnerability result. And the coefficient of determination of DRASTIC, DRASTIC–MIF, and DRASTIC–RMIF methods were 0.6, 0.4, and 0.8, respectively. From this validation DRASTIC-RMIF obtained the most accurate result among all weighting techniques due to local hydrogeological condition. Model validation showed a significant association between the sample nitrate concentration values and the DRASTIC-RMIF model index values. Decision/Policy makers must identify vulnerable zones in order to manage and maintain an identification system for groundwater supplies.

Application of geochemical tracers for the investigations of groundwater resources in semi‐arid region (Central‐East Tunisia)

AbstractGroundwater resources in Mahdia‐Ksour Essef region, located in the central‐eastern part of Tunisia, suffer from intensive exploitation and degradation of water quality. The assessment of groundwater vulnerability, the well‐understanding of geochemical processes and the investigation of groundwater quality variations are of particular importance for water resources management in this semi‐arid region. The results of this multi‐disciplinary investigation show that groundwaters of Mahdia‐Ksour Essef region are flowing from El Jem and Boumerdes regions in the South, towards the Mediterranean Sea and the sebkha of Moknine in the North. The groundwaters are classified as either Na‐Cl or Ca‐SO4. Stable oxygen and hydrogen isotope compositions (δ18O and δ2H) confirm a recharge by rapid water infiltration, evaporate surface water and water‐rock interaction processes in the salinity increase. The rock‐water interaction processes of the mineralization of groundwaters include the cation‐exchange reactions and the dissolution of carbonates and evaporate. The high values of the water quality index (WQI) and of the total dissolved solids (TDS) (3.7–11 g/L) of these groundwaters indicate their unsuitability for drinking purpose. Moreover, the combination of the WQI, TDS and nitrate results prove the vulnerability of the studied groundwater to the anthropogenic pollution linked to agriculture and domestic activities and to the salt water contamination.

GIS-based assessment of groundwater vulnerability to heavy metal contamination via water quality pollution indices in urban Aligarh, India

Abstract The study presents an assessment of groundwater vulnerability due to heavy-metal contamination using Heavy Metal Pollution and Contamination Index of Urban Aligarh. Globally, hazardous compounds in industrially contaminated sites are pressing and high-priority issue. A detailed risk assessment was carried out to determine the potential health hazards linked to locations that were recently polluted. A total of 17 groundwater samples were taken from hand-pump and 20 industrial drainage samples were collected from selected areas of Aligarh. The concentration of heavy-metals in the collected samples analyzed were shown on maps using ArcGIS software and interpreted for Heavy Metal Pollution Index (HPIx) and Contamination Index (CDx). These analyzed values were subsequently compared with the permissible limits established by the agencies like EPA, WHO, and BIS. The mean concentration of heavy-metals in groundwater of different locations was observed as follows particular sequence: Ni (1.40), Cu (0.58), Zn (0.06), Fe (0.08), Mn (0.04), Cr (0.001), Pb (0.00025) mg/l. Additionally in industrial effluent, Cr (18.3), Ni (13.34), Mn (1.16), Cu (1.99), Pb (1.2), Fe (6.3), Zn (0.51) mg/l. According to HPIx, the analysis reveals 64.7%, of visited areas belonged to have safe groundwater. Conversely, a smaller proportion, 35.3%, was found falling into heavy metal-polluted group.

A Critical Review of Climate Change Impacts on Groundwater Resources: A Focus on the Current Status, Future Possibilities, and Role of Simulation Models

The Earth’s water resources, totalling 1.386 billion cubic kilometres, predominantly consist of saltwater in oceans. Groundwater plays a pivotal role, with 99% of usable freshwater supporting 1.5–3 billion people as a drinking water source and 60–70% for irrigation. Climate change, with temperature increases and altered precipitation patterns, directly impacts groundwater systems, affecting recharge, discharge, and temperature. Hydrological models are crucial for assessing climate change effects on groundwater, aiding in management decisions. Advanced hydrological models, incorporating data assimilation and improved process representation, contribute to understanding complex systems. Recent studies employ numerical models to assess climate change impacts on groundwater recharge that could help in the management of groundwater. Groundwater vulnerability assessments vary with the spatial and temporal considerations, as well as assumptions in modelling groundwater susceptibility. This review assesses the vulnerability of groundwater to climate change and stresses the importance of accurate assessments for sustainable water resource management. It highlights challenges in assumptions related to soil and aquifer properties, multiple stressors, adaptive capacity, topography and groundwater contamination processes, gradual sea level rise scenarios, and realistic representations of the region of study. With the advancements in hydrological modelling, including the integration of uncertainty quantification and remote sensing data, artificial intelligence could assist in the efforts to improve models for assessing the impacts of climate change on hydrological modelling.

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

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

Assessing groundwater vulnerability and addressing salinization in the coastal region of Ba Ria–Vung Tau province, Vietnam: an enhanced DRASTIC model approach

Assessing groundwater vulnerability and addressing salinization in the coastal region of Ba Ria–Vung Tau province, Vietnam: an enhanced DRASTIC model approach

Groundwater Vulnerability Assessment of Shalamzar Aquifer using GIS-Based DRASTIC Model

Groundwater Vulnerability Assessment of Shalamzar Aquifer using GIS-Based DRASTIC Model