Evaluation Of Groundwater Vulnerability Research Articles

Evaluating groundwater vulnerability and assessing its quality for sustainable management

Areas with a dry climate constitute about 15% of the Earth's surface, so groundwater can be considered a safe alternative available for people who are living in these areas. Groundwater has special advantages compared to surface water in terms of spatiotemporal presence, high stability, easy access, and often of high quality and capable of resisting pollution and could be the alternative to solve the problem of water shortage.The current study evaluated Irrigation Water Quality Indices (WQIs) as well as the predicting of GIS maps to evaluate groundwater resources for agricultural uses in Al-Najaf city. 24 samples were taken from the existing wells and examined for the characteristics relating the groundwater quality. Total hardness (TH), Sodium Adsorption Ratio (SAR), Residual Sodium Carbonate (RSC), Soluble Sodium Percentage (SSP), Magnesium Hazard (MH), Permeability Index (PI), and Kelley's Index (KI) were among the irrigation indices that were assessed and evaluated. The results showed that 95.8% of sites fall within the region of extremely high salinity danger /low sodium, and 4.2% of sites fall onto the medium sodium water class, Concerning SSP and RSC all samples are considered of good quality, 95.8% of samples are suitable for irrigation based on Kelly's Ratio index, while only 4.2% regarded unsuitable. The final WQIs values were exported to the ArcMap software to create the final study area's water quality indices maps. Conducting spatial variability of groundwater quality is essential for making reliable groundwater quality interpretations and for making accurate predictions of quality at any particular site, there must be a continuous salinity and contaminants concentrations checking up calculations in case there were a need for groundwater desalination process.

Synthesizing vulnerability indices within a diverse lithological context: Corollaries for groundwater quality assurance and surface layer corrosiveness of Lokoja Geomaterials, Nigeria

ABSTRACT This study provides prototypical evaluation of groundwater vulnerability to contamination and soil corrosivity in Lokoja region, central Nigeria. By combining the aquifer vulnerability index, integrated electrical conductivity, groundwater confinement overlying strata depth to water table (GOD), and electrical anisotropy coefficient (λ) derived from lithological composition, resistivity, and layer thickness; the study identifies substantial vulnerabilities in the groundwater resources. Findings indicate that over 70% of the region is moderately to very highly vulnerable to groundwater pollution, especially in the eastern and southern parts, highlighting the need for tailored groundwater management strategies in highly vulnerable areas, covering 40% of the region. Corrosion potential varies spatially, with 80% of the upper layer being minimally corrosive and around 45% of the lower moisture-rich layer showing moderate to significant corrosiveness, emphasizing risks in central and northern zones associated with lithological compositions and moisture content. These accentuate the necessity of rigorous monitoring programs and strict land use regulations to protect aquifers and infrastructure. This research underscores the value of proactive management for safeguarding groundwater resources, providing an invaluable framework for decision-making and resource allocation to tackle contamination and corrosion risks. Importantly, the research addresses a significant research gap in a region with limited scientific exploration.

A three-step modification of the DRASTIC model using spatial multi criteria decision making methods to assess groundwater vulnerability

Groundwater vulnerability assessment, as a key tool, is essential for assisting decision-makers and experts in identifying highly vulnerable areas and devising efficient pollution reduction strategies. The widely utilized DRASTIC model for assessing groundwater vulnerability incorporates seven key geological and hydrological parameters. To address the limitations of the DRASTIC model, this study proposes a novel three-step modification by introducing an extra parameter, adjusting default weights, and utilizing alternative aggregation methods. These modifications aim to capture the unique characteristics of a specific region more accurately. The first step involves incorporating the Land Use (LU) parameter as the eighth parameter in the DRASTIC model, resulting in an updated 8-parameter model. The second step involves integrating the Analytic Hierarchy Process (AHP) to adjust parameter weights based on input from local experts. Lastly, while the Weighted Linear Combination (WLC) technique has conventionally been used for aggregating layers in the GIS environment, this study suggests employing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Furthermore, to consider decision makers' risk attitudes, the Ordered Weighted Averaging (OWA) method is utilized.To assess its effectiveness, the modified model was applied to Khoy County in Iran. Then, the results were compared to the DRASTIC model using correlation analysis based on nitrate concentrations. The results indicated a correlation coefficient of 0.67 for the modified model compared to 0.47 for the DRASTIC model. This suggests that the proposed modified model is an enhanced and highly effective approach for evaluating groundwater vulnerability.

Evaluation of groundwater vulnerability in the Rachna Doab using a modified DRASTIC model: a comparative analysis

Evaluation of groundwater vulnerability in the Rachna Doab using a modified DRASTIC model: a comparative analysis

Evaluation of Groundwater Vulnerability of Yishu River Basin Based on DRASTIC-GIS Model

The evaluation of vulnerability is a crucial aspect in the sustainable development, utilization, and preservation of groundwater resources. This study utilizes a comprehensive approach, integrating systematic analysis of hydrogeological conditions and the utilization of observed and collected data. The evaluation of groundwater vulnerability in the Yishu River Basin (YRB) was conducted by employing the DRASTIC model, along with the zone overlay function of GIS software. Seven evaluation indicators were considered in this assessment. The findings demonstrate that the groundwater vulnerability in the YRB can be categorized into five divisions: excellent, good, medium, poor, and very poor, accounting for 14.5%, 42.3%, 27.9%, 14.0%, and 1.3% respectively. The areas with low vulnerability are predominantly located in the eastern part of the study area, covering the largest proportion of the total area. Conversely, areas with high vulnerability are found alongside both banks of the Shu River, forming narrow strips. Although these areas have smaller overall coverage, they contain dispersed water sources that require careful attention. These research findings provide valuable scientific insights and serve as a reference for urban planning, land use management, and groundwater resource protection in the YRB. The formulation and adoption of targeted protection measures in accordance with different groundwater vulnerability zoning, the formulation of scientific groundwater resource development and utilization programs, and execution of land resource planning are of great significance from the perspective of groundwater resource protection.

Spatial evaluation of groundwater vulnerability using the DRASTIC-L model with the analytic hierarchy process (AHP) and GIS approaches in Edo State, Nigeria

The drinking of contaminated water is potentially hazardous to the well-being of humanity. Effective groundwater management depends on detecting groundwater contamination before it hits a critical point. The DRASTIC framework, modified globally to include land use (L), is utilized to evaluate groundwater vulnerability in various regions. In this study, an assessment of groundwater's susceptibility to contamination and a water quality index map to determine its fitness for Edo State have been done using the DRASTIC, DRASTIC-AHP, and DRASTIC-L-AHP models. The distinction of potential-risk water zones in Edo State, Nigeria, was made possible by the GIS that was used to create and combine several attribute maps. Results established that in the study area, very low (1,741.683 km2; 45%), low (1,741.683 km2; 10%), moderate (3,483.366 km2; 20%), and high (4,354.2075 km2; 25%) risk zones of groundwater contamination were identified on the overall DRASTIC-L-AHP map. The study found a significant pollution risk in one-fourth of the area, primarily in the Edo north and south regions of the study area. The significance of each factor for groundwater susceptibility and contamination risk was evaluated through a sensitivity analysis (SA). The SA indicated that the impact of the vadose zone is the most efficient variable in the DRASTIC-L-AHP model, with an effective weight value of 33.45% that is much larger than the theoretical value of 21.51%. The DRASTIC-L-AHP model, validated through hydrochemical analysis, is the least inaccurate and suitable for the current study area, serving as a useful pre-decisional tool for managing and preserving groundwater.

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.

Groundwater Vulnerability Mapping Using the Susceptibility Index (SI) Method and Tritium Isotopes: A Case Study of the Gharb Aquifer in Northwestern Morocco

The Gharb aquifer plays a critical role as a source of drinking water and irrigation in Morocco. However, rapid economic growth and increased use of chemical fertilizers have led to groundwater pollution and land degradation. To address this issue, a vulnerability assessment was conducted using the Susceptibility Index (SI) method. Five parameters including depth to groundwater, effective recharge, slope, soil type, and land use/land cover were considered to evaluate groundwater vulnerability. The vulnerability assessment revealed index values ranging from 31 to 160. The study area was categorized into three zones of relative vulnerability (low, moderate, and high). Spatial analysis demonstrated significant spatial heterogeneity, with moderate vulnerability observed in areas characterized by shallow groundwater and composed primarily of sandstones in the northwest and southwest regions. In the entire study area, the low, medium, and high vulnerability zones covered 3%, 70%, and 26% (101 km2, 2725 km2, and 986 km2), respectively. Furthermore, Tritium isotope analysis and nitrate content were selected and applied as pollution markers to confirm and validate the obtained vulnerability map. The Tritium (3H) content in groundwater reveals a correlation with an R2 value of 0.86 with the degree of vulnerability, while the nitrate concentration in the aquifer’s groundwater showed a correlation with an R2 value of 0.55.

Evaluation of Groundwater Vulnerability to Pollution Using the DRASTIC Model and GIS in the Plain Part of the Khazir River Basin, Northern Iraq

Evaluation of Groundwater Vulnerability to Pollution Using the DRASTIC Model and GIS in the Plain Part of the Khazir River Basin, Northern Iraq

An Evaluation of Groundwater Vulnerability Utilizing GIS-Based Model

Effective groundwater management requires assessing vulnerability to pollution. While the SINTACS method is widely used, it has limitations by not adequately considering hydrogeological parameters and supplementary data. To address SINTACS limitations, a modified approach (MSVILuLn) incorporates land use/cover and lineaments. Parameter weights were determined using analytic hierarchy process (MSVILuLn-AHP) and network process (MSVILuLn-ANP). Raster layers of nine parameters were analyzed in GIS to evaluate groundwater vulnerability index using SINTACS, MSVILuLn, MSVILuLn-AHP, and MSVILuLn-ANP. Nitrate concentrations from 48 wells were compared to validate results. MSVILuLn-ANP identified more very high/low vulnerability zones compared to others. It showed highest accuracy (91.7%) correlating vulnerability and nitrate levels. MSVILuLn-ANP offers a more comprehensive vulnerability assessment for groundwater management in Raipur city. Integrating SINTACS with GIS and objective weighting methods enhances spatial analysis of sensitive areas and prevents contamination.

Application of Modified DRASTIC Method for the Assessment and Validation of Confined Aquifer Vulnerability in Areas with Diverse Quaternary Deposits

Accurate vulnerability assessment methods are essential for effective groundwater management and protection, allowing the identification of areas vulnerable to pollution. The widely used DRASTIC method has been modified to improve groundwater vulnerability assessment in regions where Quaternary sediments form a confining layer above the main useful aquifer. This study applied the modified DRASTIC method to two study areas in Estonia with heterogenous Quaternary sediments. The results were compared to the original DRASTIC method and a groundwater vulnerability assessment method used formerly in Estonia. The results significantly improved with the modified version compared to the original method. The modified method also exhibited stronger correlations with nitrate concentration data, illustrating the higher accuracy of the modified DRASTIC method in vulnerability assessment in regions with confined aquifers. The results highlight the significance of modifying the vulnerability assessment methods according to regional geological conditions to evaluate groundwater vulnerability accurately and support informed decision-making in groundwater management and protection.

A modified DRASTIC model for groundwater vulnerability assessment using connecting path and analytic hierarchy process methods.

Groundwater plays a vital role in supporting water for the different needs of domestic, agricultural, and industrial sectors, and its vulnerability assessment to pollution is a valuable tool for establishing protective and preventive management. DRASTIC is a well-known GIS-based model for assessing groundwater vulnerability to pollution, which uses seven parameters including depth-to-water level, net recharge, aquifer media, soil media, topography, the impact of the vadose zone, and hydraulic conductivity. The predefined weights of DRASTIC parameters have made a barrier to its applicability for different regions with different hydroclimatic conditions. To overcome this problem, it has been suggested to apply analytic hierarchy process (AHP) method for modifying the model by adjusting the weights of the parameters. AHP is a widely used method to elicit experts' judgments about different involving parameters through constructing pairwise comparison matrixes (PCMs). Since AHP calculates the weights by performing pairwise comparisons between the parameters, achieving consistent comparisons is difficult when the number of parameters increases. The objective of this research is to modify the DRASTIC model by integrating the connecting path method (CPM) and AHP. The proposed methodology involves asking experts to perform a number of pairwise comparisons between the parameters and then construct an incomplete PCM using the obtained information. To complete the missing values in the PCM, CPM is employed. The CPM is an effective approach that not only estimates missing judgments but also ensures minimal geometric consistency. The proposed method along with DRASTIC and pesticide DRASTIC models is applied to Khoy County, which is located in the northwest part of Iran. The efficiency of the proposed method was further confirmed through the results of the Pearson coefficient test conducted on nitrate concentrations. The test revealed correlation values of 0.47, 0.27, and 0.57 for DRASTIC, pesticide DRASTIC, and modified DRASTIC, respectively. These results demonstrated that the proposed method provides a more precise evaluation of groundwater vulnerability.

Evaluation of Groundwater Vulnerability in the Upper Kelkit Valley (Northeastern Turkey) Using DRASTIC and AHP-DRASTICLu Models

This study aimed to investigate groundwater vulnerability to pollution in the Upper Kelkit Valley (NE Turkey). For this purpose, vulnerability index maps were created using the generic DRASTIC and AHP-DRASTICLu models. The latter model was suggested by adding a parameter to the DRASTIC model and weighting its parameters with the analytical hierarchy process with the GIS technique. The results showed that areas with high and very high vulnerabilities are concentrated around the Kelkit Stream, which flows from east to west in the central part of the study area. In contrast, areas with low and very low vulnerability classes are located in the northern and southern parts of the study area. To validate the model results, a physicochemical characterization of groundwater samples and their corresponding vulnerability index values were statistically compared using the Spearman correlation method. In addition, the single-parameter sensitivity method was applied to analyze the models’ sensitivities. Results revealed a stronger correlation between the vulnerability index values of the AHP-DRASTICLu model (compared to the DRASTIC model) in terms of sulfate (R2 = 0.75) and chloride (R2 = 0.76), while there was a slightly weaker correlation for the electrical conductivity (R2 = 0.65) values of the groundwater samples. Sensitivity analysis indicated that the vadose zone, aquifer media, and land use are the most influential parameters responsible for the highest variation in the vulnerability index. Generally speaking, the results indicated that the AHP-DRASTICLu model performs better than the DRASTIC model for investigating groundwater vulnerability to pollution in the Upper Kelkit Valley.

Z-numbers based novel method for assessing groundwater specific vulnerability

Groundwater vulnerability assessment systems are developed to achieve a suitable method for protecting groundwater resources from contaminants. One of the well-known approaches for determining groundwater susceptibility is the DRASTIC method. This method considers seven effective parameters to evaluate groundwater vulnerability. Since groundwater contamination is often associated with uncertainty, this study applied the concept of the Z-number as a new generation of Fuzzy Logic (FL) to estimate the specific vulnerability of the aquifers. Unlike conventional FL models, which do not incorporate reliability, the Z-numbers include information constraint and reliability and can effectively explain uncertainty in human knowledge. To highlight this approach, the DRASTIC parameters (inputs) and nitrate concentration values (output) were used through two scenarios to estimate the specific vulnerability of the Ardabil and the Qorveh-Dehgolan plains (QDP) and the obtained results were compared with DRASTIC model as a benchmark model. The analysis of the results showed that the Z-number Based Modeling (ZBM), in addition to superiority to DRASTIC model, improved the quality of results compared to the classic FL by 53% (using seven inputs), 184% (using four inputs) in the Ardabil plain, and 127% (using seven inputs), 311% (using four inputs) in the QDP due to the consideration of data reliability and appropriate weighting of the rules. Also, the quality of the extracted Z-number-based rules in plains with high CV may be lower (such as the high CV of the Ardabil compared to the QDP). Therefore, the results of ZBM may not show a significant improvement over the conventional FL.

Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta

AbstractGroundwater is the primary source of water in the Bengal Delta but contamination threatens this vital resource. In deltaic environments, heterogeneous sedimentary architecture controls groundwater flow; therefore, characterizing subsurface structure is a critical step in predicting groundwater contamination. Here, we show that surface information can improve the characterization of the nature and geometry of subsurface features, thus improving the predictions of groundwater flow. We selected three locations in the Bengal Delta with distinct surface river network characteristics—the lower delta with straighter tidal channels, the mid‐delta with meandering and braided channels, and the inactive delta with transitional sinuous channels. We used surface information, including channel widths, depths, and sinuosity, to create models of the subsurface with object‐based geostatistical simulations. We collected an extensive set of lithologic data and filled in gaps with newly drilled boreholes. Our results show that densely distributed lithologic data from active lower and mid‐delta are consistent with the object‐based models generated from surface information. In the inactive delta, metrics from object‐based models derived from surface geometries are not consistent with subsurface data. We further simulated groundwater flow and solute transport through the object‐based models and compared these with simulated flow through lithologic models based only on variograms. Substantial differences in flow and transport through the different geologic models show that geometric structure derived from surface information strongly influences groundwater flow and solute transport. Land surface features in active deltas are therefore a valuable source of information for improving the evaluation of groundwater vulnerability to contamination.

A Numerical Approach to Evaluating Groundwater Vulnerability to Seawater Intrusion on Jeju Volcanic Island, South Korea

Seawater intrusion (SWI) is a critical issue for coastal aquifers, especially in islands where groundwater is the sole source of water supply. The objective of this study was to develop a straightforward approach to evaluating groundwater vulnerability to SWI, using a statistical method with spatial analyses applied to the four basins of Jeju volcanic island. In this study, five factors were parametrized, including hydraulic conductivity, groundwater level, distance from shoreline to wells, well depth and groundwater use. These parameters were spatially interpolated and correlated with groundwater electrical conductivity as a proxy for groundwater salinization, resulting in three parameters with significant relations: groundwater use, well depth, and groundwater level. Then, a numerical model for the SWI vulnerability assessment was constructed using ratings and weights, and by evaluating the vulnerability as weak, moderate and high with a numerical index. Regional conditions, including major land-use types, industrial activities, population and the degree of urbanisation, could affect parameters differently at each region. Based on the percentage of area with a high vulnerability, regions of Jeju Island followed the order of eastern > northern > western > southern, indicating that preventive measures for SWI and its influencing parameters could be applied more effectively in certain regions.

Evaluation of groundwater vulnerability using GIS-based DRASTIC model in Greater Monrovia, Montserrado County, Liberia

To ensure that groundwater resources are effectively protected and to improve the quality of life, it is vital to take into consideration all polluting activities that could pose a potential risk to the resource. Groundwater potential research conducted only covers 5% of Montserrado County excluding Greater Monrovia in Liberia. Although this little percentage of groundwater potential research is well known, studies on the vulnerability of the aquifer to pollution are non-existent. Therefore, this study aims at assessing groundwater vulnerability in Greater Monrovia, Montserrado County, Liberia, which will help in optimizing water well drilling activities and protecting the resource. A groundwater vulnerability map for the study area using the Geographic Information System (GIS) based DRASTIC Model was developed and the results suggest that 73% of the study area is very sensitive to pollution, whereas 15% and 11% are moderately and weakly sensitive to pollution, respectively. The key pollution areas identified within the study area were communities of intensive anthropogenic activities and associated geological contamination. The effectiveness of the GIS-based DRASTIC Model in groundwater vulnerability assessment was validated and nearly 60% of the wells contained fluoride concentrations that exceeded the Liberia Water Quality Standard (LWQS) permissible limit. The findings suggest that even though the water table is relatively shallow, future projects in the high and moderate sensitivity zones should be handled carefully. Planners, groundwater managers, and decision-makers may utilize the maps created by this study as a general point of reference for vulnerability when making attempts to safeguard this delicate resource.

Regional Scale Assessment of Shallow Groundwater Vulnerability to Contamination from Unconventional Hydrocarbon Extraction.

Concerns over unconventional oil and gas (UOG) development persist, especially in rural communities that rely on shallow groundwater for drinking and other domestic purposes. Given the continued expansion of the industry, regional (vs local scale) models are needed to characterize groundwater contamination risks faced by the increasing proportion of the population residing in areas that accommodate UOG extraction. In this paper, we evaluate groundwater vulnerability to contamination from surface spills and shallow subsurface leakage of UOG wells within a 104,000 km2 region in the Appalachian Basin, northeastern USA. We test a computationally efficient ensemble approach for simulating groundwater flow and contaminant transport processes to quantify vulnerability with high resolution. We also examine metamodels, or machine learning models trained to emulate physically based models, and investigate their spatial transferability. We identify predictors describing proximity to UOG, hydrology, and topography that are important for metamodels to make accurate vulnerability predictions outside their training regions. Using our approach, we estimate that 21,000-30,000 individuals in our study area are dependent on domestic water wells that are vulnerable to contamination from UOG activities. Our novel modeling framework could be used to guide groundwater monitoring, provide information for public health studies, and assess environmental justice issues.

Impacts of Coastal Shrimp Ponds on Saltwater Intrusion and Submarine Groundwater Discharge

AbstractShrimp aquaculture has expanded rapidly in coastal zones worldwide over the past few decades. Saline water stored in shrimp farm ponds can infiltrate into the underlying aquifer causing groundwater salinization and increased submarine groundwater discharge (SGD) to coastal water. However, little research has assessed salinization resulting from these shrimp ponds. To understand the impacts of shrimp farm irrigation on groundwater salinization and SGD, we numerically simulated a series of aquaculture management scenarios in a two‐dimensional conceptual coastal aquifer using a coupled surface‐subsurface approach. We characterized sensitivities to pond water salinity, pond water depth, and farm width. Salinization was assessed by three indicators (salinized area, infiltrated salt mass, and recovery rate), and three SGD indicators were evaluated (fresh SGD, saline SGD, and saltwater circulation rate). Our results show that pond water depth is the primary control on the mass of saltwater infiltration while farm width is the primary control for recovery rate. Pond water salinity and depth affect both fresh and saline SGD. We show that aquaculture is a previously unrecognized mechanism of salinization affecting coastal aquifer vulnerability and SGD. A regional graphical information system analysis shows transformation into aquacultural ponds could introduce considerable SGD variability spatially and temporally. These findings will enable coastal managers to better evaluate groundwater vulnerability in regions with expanding onshore aquaculture and demonstrates the impact of aquaculture on coastal groundwater resources and the need for further study to understand the impact of aquaculture across Asia and the globe.

Evaluation of groundwater vulnerability and soil corrosivity of the Coastal Plain Sands, case of Delta State, Niger Delta South-South Nigeria

Evaluation of groundwater vulnerability and soil corrosivity of the Coastal Plain Sands, case of Delta State, Niger Delta South-South Nigeria