Aquifer Vulnerability Assessment for Sustainable Groundwater Management Using DRASTIC

Empirical relationship between vadose zone properties and diesel attenuation capacity: A complement for intrinsic vulnerability models

Evaluating and predicting the natural attenuation capacity (AC) of a vadose zone is essential for determining groundwater vulnerability to contamination from upper sources. However, it remains unclear how the physicochemical properties of vadose zone soils affect AC owing to their complexity and spatial heterogeneity. In this study, we developed a regression model for estimating the AC of a vadose zone against diesel using datasets from different soils with a wide range of physicochemical properties. Among the 17 properties, six (i.e., organic matter (OM), total phosphorous (TP), coefficient of uniformity, particle size (D30), van Genuchten's n, saturation degree (SD)) were selected as primary regressors. The results indicate that biogeochemical factors, including OM and TP, have decisive effects on the AC. Finally, the regression model was expanded to a GIS-based spatial model and applied to Namyangju, Korea using the index-overlay method. The produced AC map showed a nonmonotonic decrease along the depth, and the areas closer to the water bodies generally represented low AC values, most likely due to the lower OM, TP, and higher SD. This study provides an empirical basis for future research initiatives for spatial and temporal AC dynamics, which complements conventional intrinsic groundwater vulnerability models such as DRASTIC.

Integrated assessment of groundwater vulnerability in arid areas combining classical vulnerability index and AHP model

Groundwater is the main source of water for agriculture, industry, and families in arid areas. At present, there is an urgent need to protect groundwater due to human activities. In this study, the Qingshui River Basin was selected as the study area. Based on the DRASTIC model, the DRASTIC-Land use type (DRASTICL) model and the analytic hierarchy process-DRASTICL (AHP-DRASTICL) model were constructed by optimizing the indicators and weights. And the three models were applied to calculate the groundwater vulnerability index (GVI), and the groundwater vulnerability map (GVM) was drawn. The validation results of Spearman correlation coefficient show that the DRASTICL model and the AHP-DRASTICL model have higher correlation, which indicates that the optimized model is more accurate. Among them, the AHP-DRASTICL model has the highest correlation coefficient (ρ = 0.92), which is more in line with the actual situation. The results of this study can provide scientific guidance for the protection and utilization of groundwater in the Qingshui River Basin. And it is of guiding significance for the study of groundwater vulnerability, especially for groundwater management in arid and semi-arid areas.

Assessing long-term ecological impacts of PCE contamination in groundwater using a flow cytometric fingerprint approach

This study aims to develop and validate a comprehensive method for assessing ecological disturbances in groundwater ecosystems caused by tetrachloroethylene (PCE) contamination, utilizing flow cytometry (FCM) fingerprint approach. We hypothesized that the ecological disturbance resulting from PCE contamination would exhibit 'press disturbance', persisting over extended periods, and inducing notable phenotypic differences in the microbial community compared to undisturbed groundwater. We collected 40 groundwater samples from industrial district with a history of over twenty years of PCE contamination, along with 56 control groundwater from the national surveillance groundwater system. FCM revealed significant alterations in the phenotypic diversity of microbial communities in PCE-contaminated groundwater, particularly during the dry season. The presence of specific dechlorinating bacteria (Dehalococcoides, Dehalogenimonas, and Geobacter) and their syntrophic partners was identified as an indicator of contamination. Phenotypic diversity measures provided clearer and more direct reflections of contamination impact compared to taxonomic diversity measures. This study establishes FCM fingerprinting as a simple, robust, and accurate method for evaluating ecological disturbances, with potential applications in early warning systems and continuous monitoring of groundwater contamination. The findings not only underscore the sensitivity of FCM in detecting phenotypic variations induced by environmental stressors but also highlight its utility in understanding the complex dynamics of microbial communities in contaminated groundwater ecosystems.

Integrated SEAWAT model and GALDIT method for dynamic vulnerability assessment of coastal aquifer to seawater intrusion

Seawater intrusion (SI) has become a global issue exacerbated by intense anthropogenic activities and climate change. It is imperative to seek a synergistic strategy to reconcile environmental and economic benefits in the coastal regions. However, the intricate SI process and data scarcity present formidable challenges in dynamically assessing the coastal groundwater vulnerability. To address the challenge, this study proposed a novel framework that integrates the existing vulnerability assessment method (GALDIT) and variable-density groundwater model (SEAWAT). The future scenarios from 2019 to 2050 were investigated monthly under climate change (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and human activities (80 % and 50 % of current groundwater abstraction) in Longkou city, China, a typical coastal region subject to extensive SI, compared with the status quo in 2018. Results indicated that by 2050, the high vulnerability area, is in a narrow buffer within 1.2 km from the shoreline and exhibits minor changes while the salt concentration here increased by about 2700 mg/L compared with the current situation. The moderate vulnerability zone expands by about 30 km2, and the low vulnerable area decreases proportionally. The groundwater over-abstraction is identified as a more critical factor compared to the regional precipitation under climate change. When groundwater abstraction is reduced to 80 % of the current scale, the expansion rate of the moderate-vulnerable area slows down significantly, with an expansion area of only 18 km2 by 2050. Further reducing groundwater abstraction to 50 % of the current scale shifts the evolution trend of the medium-vulnerable area from expansion to contraction, with the area shrinking by about 11 km2 by 2050. The integrated vulnerability assessment framework can be applied not only in the similar coastal regions but also provides insights into other natural hazards.

GIS-based multicriteria and artificial neural network (ANN) investigation for the assessment of groundwater vulnerability and pollution hazard in the Braga shallow aquifer (Central Tunisia): A critical review of generic and modified DRASTIC models

Groundwater vulnerability and pollution hazard in the Braga shallow aquifer were assessed through an integrated GIS-based multicriteria analysis and Artificial Neural Network (ANN) approach, using DRASTIC and DRASTIC-LU models. The DRASTIC model integrates seven geological parameters. The DRASTIC-LU model includes an eighth parameter in addition to the previous ones. This parameter is the land use that represents the human source of groundwater pollution. The DRASTIC map showed four classes: very low (12.06%), low (81.88%), moderate (5.16%) and high (0.9%), where the vulnerability index ranged between 43 and 159. The DRASTIC-LU vulnerability index ranged between 53 and 204 and showed five classes: very low (3.10%), low (14.06%), moderate (17.11%), high (27.08%) and very high (38.65%). The DRASTIC-LU vulnerability map indicated that the high pollution risk is imposed by the intensive vegetable cultivation and the domestic wastewater. The pollution hazard index (PHI) was calculated based on the ANN modelling, using the land-use as an input and the vulnerability as a hidden layer. The DRASTIC model-based PHI map showed six classes: rare hazard (8.6%), very low (30.97%), low (6.18%), moderate (51.45%), high (2.43%) and very high (0.37%). While, The DRASTIC-LU model-based PHI map (PHILU) showed seven classes: rare hazard (2.91%), very low (11.9%), low (12.33%), moderate (13.78%), high (9.23%), very high (15.46%) and extremely hazardous (34.39%). The validation of these maps indicated that the DRSTIC-LU-based PHI is more reliable as it accurately identifies the hazardous zones.

Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model

This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that net recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98% of the study area falls into a very high vulnerability class, 31.90% falls into a high vulnerability, 23.52% falls into the average vulnerability, 21.75% falls into a low vulnerability, and 9.85% falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution.

Pollution Vulnerability of the Ghiss Nekkor Alluvial Aquifer in Al-Hoceima (Morocco), Using GIS-Based DRASTIC Model

Groundwater resources of the alluvial aquifer Ghiss Nekkor, which covers an area of 100 km², are the main source of domestic and agricultural freshwater supply in the region of Al Hoceima in Morocco. Due to human activities (overexploitation, increase in agricultural activity), this alluvial aquifer has become very sensitive to chemical pollution. The principal objective of this current study is to develop and implement a calibration method to assess, map, and estimate the vulnerability of the Ghiss Nekkor alluvial aquifer to pollution risk. In this work, the GIS-based DRASTIC model was used to estimate the inherent vulnerability to contamination of the Ghiss Nekkor alluvial aquifer with seven standard hydrogeological parameters. Nitrate (NO₃) and electrical conductivity (EC) data were used to validate the DRASTIC map. The results of the vulnerability map analysis show that the vulnerability to contaminants varies from non-existent in the southwestern part of the plain (7.3% of the total area), to very high (14.5%). The vulnerability is moderate in the central and northeastern areas (26.9%), while it is high in the other areas (17.5%). Furthermore, the most sensitive areas are mainly concentrated near the coastal strip and the central plain on both sides of the Nekkor River. In these areas, the NO₃ and EC values are above the maximum allowable limit of the World Health Organization. The results suggest that the DRASTIC model can be an effective tool for decision-makers concerned about managing groundwater sustainability.

A comparative analysis on groundwater vulnerability models-fuzzy DRASTIC and fuzzy DRASTIC-L

Groundwater vulnerability assessment using the fuzzy logic technique is attempted in this study. A hierarchical fuzzy inference system is created to serve the selected objective. The parameters considered in this study are similar to the seven parameters used in conventional DRASTIC methods; however, the effect of land use and land cover is studied by including it as an additional parameter in a model. A hierarchy is created by comparing two input parameters, say (D and R), and the output of the same is paired as an input with the third parameter (A) and so on using the fuzzy toolbox in MATLAB. Thus, the final output of fuzzy inference systems six and seven (FI6 and FI7) is defuzzified and mapped using ArcGIS to obtain the groundwater vulnerability zones by fuzzy DRASTIC and fuzzy DRASTIC-L. Each map is grouped into five vulnerability classes: very high, high, moderate, low, and very low. Further, the results were validated using the observed nitrate concentration from 51 groundwater sampling points. The receiver operating curve (ROC) technique is adopted to determine the best suitable model for the selected study. From this, area under the curve is estimated and found to be 0.83 for fuzzy DRASTIC and 0.90 for fuzzy DRASTIC-L; the study concludes that fuzzy DRASTIC-L has a better value of AUC suits best for assessing the groundwater vulnerability in Thoothukudi District.

A modified approach to quantify aquifer vulnerability to pollution towards sustainable groundwater management in Irrigated Indus Basin

The quality of groundwater in the study watershed has worsened because of industrial effluents and residential wastes from the urbanized cities; therefore, there is an important need to explore the aquifer vulnerability to pollution for sustainable groundwater management in the Irrigated Indus Basin (IIB). This study proposed a novel methodology to quantify groundwater vulnerability using two fully independent methodologies: the first by reintroducing an improved recharge factor (R) map and the second by incorporating three different weight and rating schemes into a traditional DRASTIC framework to improve the performance of the DRASTIC approach. In the current study, we composed a recharge map from Soil and Water Assessment Tool (SWAT) output (namely SWAT recharge map) with a drainage density map to retrieve an improved composite recharge map (SWAT-CRM). SWAT-CRM along with other thematic layers was combined using weightage overlay analysis to prepare the maps of groundwater vulnerability index (VI). The weight scale (w) and rating scale (r) were assigned based on a survey of available literature, and we then amended them using the analytical hierarchy process (AHP) and a probability frequency ratio (PFR) technique. Results depicted that the region under high groundwater vulnerability was found to be 5-22% using traditional recharge maps, while those are 9-23% using improved SWAT-CRM. The area under the curve (AUC) revealed that groundwater vulnerability zones predicted with SWAT-CRM outperformed the DRASTIC model applied with the traditional recharge map. Groundwater electrical conductivity (EC) was>2500 mS/cm in the high groundwater vulnerability zones, while it was <1000 mS/cm in the low groundwater vulnerability zones. The outcomes of this study can be used to improve the sustainability of the groundwater resources in IIB through proper land-use management practices.

Denitrification in Intrinsic and Specific Groundwater Vulnerability Assessment: A Review

Several groundwater vulnerability methodologies have been implemented throughout the years to face the increasing worldwide groundwater pollution, ranging from simple rating methodologies to complex numerical, statistical, and hybrid methods. Most of these methods have been used to evaluate groundwater vulnerability to nitrate, which is considered the major groundwater contaminant worldwide. Together with dilution, the degradation of nitrate via denitrification has been acknowledged as a process that can reduce reactive nitrogen mass loading rates in both deep and shallow aquifers. Thus, denitrification should be included in groundwater vulnerability studies and integrated into the various methodologies. This work reviewed the way in which denitrification has been considered within the vulnerability assessment methods and how it could increase the reliability of the overall results. Rating and statistical methods often disregard or indirectly incorporate denitrification, while numerical models make use of kinetic reactions that are able to quantify the spatial and temporal variations of denitrification rates. Nevertheless, the rating methods are still the most utilized, due to their linear structures, especially in watershed studies. More efforts should be paid in future studies to implement, calibrate, and validate user-friendly vulnerability assessment methods that are able to deal with denitrification capacity and rates at large spatial and temporal scales.

Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms

A reliable assessment of the aquifer contamination vulnerability is essential for the conservation and management of groundwater resources. In this study, a recent technique in artificial intelligence modeling and computational optimization algorithms have been adopted to enhance the groundwater contamination vulnerability assessment. The original DRASTIC model (ODM) suffers from the inherited subjectivity and a lack of robustness to assess the final aquifer vulnerability to nitrate contamination. To overcome the drawbacks of the ODM, and to maximize the accuracy of the final contamination vulnerability index, two levels of modeling strategy were proposed. The first modeling strategy used particle swarm optimization (PSO) and differential evolution (DE) algorithms to determine the effective weights of DRASTIC parameters and to produce new indices of ODVI-PSO and ODVI-DE based on the ODM formula. For strategy-2, a deep learning neural networks (DLNN) model used two indices resulting from strategy-1 as the input data. The adjusted vulnerability index in strategy-2 using the DLNN model showed more superior performance compared to the other index models when it was validated for nitrate values. Study results affirmed the capability of the DLNN model in strategy-2 to extract the further information from ODVI-PSO and ODVI-DE indices. This research concluded that strategy-2 provided higher accuracy for modeling the aquifer contamination vulnerability in the study area and established the efficient applicability for the aquifer contamination vulnerability modeling.

Mapping Interflow Potential and the Validation of Index-Overlay Weightings by Using Coupled Surface Water and Groundwater Flow Model

Interflow is an important water source contributing to river flow. It directly influences the near-surface water cycles for water resource management. This study focuses on assessing the interflow potential and quantifying the interflow in the downstream area along the Kaoping River in southern Taiwan. The interflow potential is first determined based on the modified index-overlay model, which employs the analytical hierarchy process (AHP) to calculate the ratings and weightings of the selected factors. The groundwater and surface water flow (GSFLOW) numerical model is then used to link the index-overlay model to quantify the interflow potential for practical applications. This study uses the Monte Carlo simulations to assess the influence of rainfall-induced variations on the interflow uncertainty in the study area. Results show that the high potential interflow zones are located in the high to middle elevation regions along the Kaoping River. Numerical simulations of the GSFLOW model show an interflow variation pattern that is similar to the interflow potential results obtained from the index-overlay model. The average interflow rates are approximately 3.5 × 104 (m3/d) in the high elevation zones and 2.0 × 104 (m3/d) near the coastal zones. The rainfall uncertainty strongly influences interflow rates in the wet seasons, especially the peaks of the storms or heavy rainfall events. Interflow rates are relatively stable in the dry seasons, indicating that interflow is a reliable water resource in the study area.

Pollution threat to water and soil quality by dumpsites and non-sanitary landfills in Brazil: A review

This work presents an overview of environmental studies performed in areas affected by dumpsites and non-sanitary landfills in Brazil, focusing on physicochemical analysis of surface water, groundwater, and soils, as well as geophysical surveys. The objective was to identify the main contaminants found in these areas and to assess their environmental impact, guiding possible intervention measures, indicating the priority areas, and showing whether post-closure activities are mandatory. The results should support governmental actions, especially considering the recent approval of Brazil's new sanitation framework. The present review assessed 162 publications, which described 104 different municipal solid waste (MSW) disposal sites. The physicochemical parameters of analyzed surface water, groundwater, and soil samples were above Brazilian legislation levels in 74%, 70%, and 24% of the studies, respectively. The parameters more frequently above permissible levels were coliforms, biochemical oxygen demand, dissolved oxygen, and phosphorus for surface water; lead, coliforms, and iron for groundwater; copper, cadmium, lead, and zinc for soil. The results indicated that Brazilian dumpsites are causing negative impacts in surrounding soils and water resources, posing ecological and public health risks that persist even after the site's closure. Considering that this study provides only a reduced scenario, the dimension of this environmental problem in Brazil is noteworthy. Therefore, it is suggested that not only inadequate disposal is prohibited, but also efficient enforcement methods are adopted and aftercare is appropriately regulated in the country, making it obligatory to establish monitoring plans and implement mitigation techniques to avoid abandoning potentially contaminated areas.

Assessment of groundwater intrinsic vulnerability using GIS-based DRASTIC method in District Haripur, Khyber Pakhtunkhwa, Pakistan

The stress on the freshwater resources of the planet earth has led the United Nations to add a goal regarding clean water in sustainable development goals list in order to address the global availability of clean water. The widespread use of fertilizers and industrial effluents caused the groundwater contamination in the Haripur District, Khyber Pakhtunkhwa, Pakistan. To investigate and assess the vulnerability of groundwater to contamination, geographic information system (GIS)-based DRASTIC model has been employed. The DRASTIC index values lie between 88 and 190. The lower the DI value, the lower will be the susceptibility towards pollution and vice versa. The indices were classified into five zones, i.e., low (< 109), medium (110-129), moderate (130-149), high (150-169), and very high vulnerable zones (> 170) on the basis of equal intervals. The low vulnerable zone covers almost 6% of the study area, i.e., 118 km². Medium vulnerable zone encompasses an area of approximately 23%, i.e., 506 km². The moderate vulnerable zone is the largest in the district covering almost 965 km², approximately 45% of the study area. The high and very high vulnerable zone encompasses almost 23% and 3% of the study area which means 506 km² and 66 km² respectively. A spatial distribution map was generated for nitrate concentration to validate the DRASTIC indices. The results demonstrate a fair relation between groundwater susceptibility and spatial nitrate distribution. This index map will provide a baseline study for this area to develop the safe zones for groundwater exploitation and controlling the current state of deterioration of environmental norms. The areas of high vulnerability are the firsthand task to improve the current situation of crisis especially in the southern parts such as the Hattar industrial area and its surroundings drained by those effluents. These further need specific tasks to restore and reclaim the polluted ecosystem by using proper technological solutions for disposal of these effluents.

Estimating Soil Water Susceptibility to Salinization in the Mekong River Delta Using a Modified DRASTIC Model

Saltwater intrusion risk assessment is a foundational step for preventing and controlling salinization in coastal regions. The Vietnamese Mekong Delta (VMD) is highly affected by drought and salinization threats, especially severe under the impacts of global climate change and the rapid development of an upstream hydropower dam system. This study aimed to apply a modified DRASTIC model, which combines the generic DRASTIC model with hydrological and anthropogenic factors (i.e., river catchment and land use), to examine seawater intrusion vulnerability in the soil-water-bearing layer in the Ben Tre province, located in the VMD. One hundred and fifty hand-auger samples for total dissolved solids (TDS) measurements, one of the reflected salinity parameters, were used to validate the results obtained with both the DRASTIC and modified DRASTIC models. The spatial analysis tools in the ArcGIS software (i.e., Kriging and data classification tools) were used to interpolate, classify, and map the input factors and salinization susceptibility in the study area. The results show that the vulnerability index values obtained from the DRASTIC and modified DRASTIC models were 36–128 and 55–163, respectively. The vulnerable indices increased from inland districts to coastal areas. The Ba Tri and Binh Dai districts were recorded as having very high vulnerability to salinization, while the Chau Thanh and Cho Lach districts were at a low vulnerability level. From the comparative analysis of the two models, it is obvious that the modified DRASTIC model with the inclusion of a river or canal network and agricultural practices factors enables better performance than the generic DRASTIC model. This enhancement is explained by the significant impact of anthropogenic activities on the salinization of soil water content. This study’s results can be used as scientific implications for planners and decision-makers in river catchment and land-use management practices.

Groundwater vulnerability mapping using the modified DRASTIC model: the metaheuristic algorithm approach

Vulnerability assessment and mapping is a significant tool for sustainable management of the precious natural groundwater resources. DRASTIC is an extensively used index model to map groundwater vulnerable zones. However, the original DRASTIC model rates and weights used in most of the research depict the poor correlation between nitrate concentration and groundwater vulnerability index. Wilcoxon test and five population-based metaheuristic (MH) algorithms, namely, firefly algorithm (FA), invasive weed optimization (IWO), teaching learning-based optimization (TLBO), shuffled frog leaping algorithm (SFLA), and particle swarm optimization (PSO), were used to optimize the rates and weights of the DRASTIC model to improve its accuracy. The performance of all the employed metaheuristic algorithms converges to a global optimal solution at different iterations, and to choose the best algorithm for DRASTIC weights optimization, a ranking methodology was proposed. The algorithms were ranked by calculating the relative closeness of alternatives with computational speed and the number of iterations as attributes in the TOPSIS method. This study identifies FA as the outperforming algorithm among the employed for this specified weight optimization problem based on ranking. The result of the optimization model proposed depicts significant improvement in the correlation coefficient between the groundwater vulnerability index and nitrate concentration from 0.0545 for the original DRASTIC model to 0.7247 for the Wilcoxon-MH- DRASTIC. Hence, this ranking approach can be adopted when global optimal solution is found by all employed algorithms in DRASTIC weight optimization.

A Novel Approach to Harmonize Vulnerability Assessment in Carbonate and Detrital Aquifers at Basin Scale

The DRASTIC (D: Depth to water; R: Net recharge; A: Aquifer media; S: Soil media; T: Topography; I: Impact of vadose zone; C: Hydraulic conductivity) index is usually applied to assess intrinsic vulnerability in detrital and carbonate aquifers, although it does not take into account the particularities of karst systems as the COP (C: Concentration of flow; O: Overlying layers above water table; P: precipitation) method does. In this paper we aim to find a reasonable correspondence between the vulnerability maps obtained using these two methods. We adapt the DRASTIC index in order to obtain reliable assessments in carbonate aquifers while maintaining its original conceptual formulation. This approach is analogous to the hypothesis of “equivalent porous medium”, which applies to karstic aquifers the numerical solution developed for detrital aquifers. We applied our novel method to the Upper Guadiana Basin, which contains both carbonate and detrital aquifers. Validation analysis demonstrated a higher confidence in the vulnerability assessment provided by the COP method in the carbonate aquifers. The proposed method solves an optimization problem to minimize the differences between the assessments provided by the modified DRASTIC and COP methods. Decision trees and spatial statistics analyses were combined to identify the ranges and weights of DRASTIC parameters to produce an optimal solution that matches the COP vulnerability classification for carbonate aquifers in 75% of the area, while maintaining a reliable assessment of the detrital aquifers in the Basin.

Pollution characteristics of aromatic hydrocarbons in the groundwater of China

Much of the world's groundwater supply has been contaminated by aromatic hydrocarbons originating from anthropogenic sources. To study the occurrence and distribution characteristics of aromatic hydrocarbons in groundwater, 24 aromatic hydrocarbon compounds were selected: Five BTEX compounds (benzene, toluene, ethylbenzene, o-xylene, m-xylene, and p-xylene), 10 alkyl-substituted benzene, and 9 halogenated aromatics. These aromatic hydrocarbons were then analyzed from 355 samples collected from across China. Results indicated that aromatic hydrocarbons were detected in 59 out of 355 samples. Of the selected aromatic hydrocarbons, BTEX compounds were detected with high frequency and at low concentrations; comparatively, halogenated aromatics were detected with low frequency and at high concentrations. The aromatic hydrocarbon characteristics found in both karst and pore groundwater samples were then determined using their respective hydrogeological conditions and corresponding human activities. In karst groundwater, BTEX compounds were the most frequently detected aromatic hydrocarbon. The high detection frequencies of aromatic hydrocarbons were caused by their rapid migration, owing to the developed conduit system in the sampled karst area. The low concentrations of aromatic hydrocarbons in karst groundwater samples were caused by low-intensity human activity along with special hydrogeological conditions with higher redox potential and the unique compositions of aromatic hydrocarbons. Alkyl-substituted aromatics and halogenated aromatics were detected at higher concentrations in pore groundwater, owing to high-intensity human activity. Aromatic hydrocarbon pollution was gradually decreased along piedmont-alluvial plain-coast line, owing to a decrease in aquifer vulnerability. These were positively correlated with the size of the aquifer's particles. Samples with a high accumulative concentration of these aromatic hydrocarbons tended to occur in pore groundwater with a high concentration of either SO₄^2- or Cl^-.

A multi-approach assessment of land use effects on groundwater quality in a karstic aquifer

Groundwater represents almost half of the drinking water worldwide and more than one third of water used for irrigation. Agro-industrial activities affect water resources in several manners; one of the most important is leaching of agrochemical residues. This research identifies the major contributors of changes in groundwater quality comparing two contrasting land uses in a karstic area of the Yucatan peninsula as case study. Using a multiple approach, we assess the impact of land use with physicochemical data, multivariate analyses, hydrogeochemistry and nitrate isotopic composition. We confirmed that agricultural land use has a greater impact on groundwater quality, observed in higher concentration of nitrates, ammonium, potassium and electrical conductivity. Seasonality has an influence on phosphates and the chemical composition of the groundwater, increasing the concentration of dissolved substances in the rainy season. There was a clear effect of manure application in the agricultural zone and the nitrate isotopic composition of groundwater points toward recharge in certain areas. We consider that seasonality and land use effects are intertwined and sometimes difficult to separate, likely because of land use intensity and hydrogeochemical process at a local scale. Finally, we observed poor groundwater quality in the agricultural area during the wet season; thus, it is desirable to maintain non-agricultural areas that provide groundwater of appropriate quality.

Assessing Groundwater Vulnerability: DRASTIC and DRASTIC-Like Methods: A Review

Groundwater vulnerability studies are sources of essential information for the management of water resources, aiming at the water quality preservation. Different methodologies for estimating the groundwater vulnerability, in general, or of the karst aquifer, in particular, are known. Among them, DRASTIC is one of the most popular due to its performance and easy-to-use applicability. In this article, we review DRASTIC and some DRASTIC-like methods introduced by different scientists, emphasizing their applications, advantages, and drawbacks.

Modification of the DRASTIC Framework for Mapping Groundwater Vulnerability Zones

The DRASTIC technique is commonly used to assess groundwater vulnerability. The main disadvantage of the DRASTIC method is the difficulty associated with identifying appropriate ratings and weight assignments for each parameter. To mitigate this issue, ratings and weights can be approximated using different methods appropriate to the conditions of the study area. In this study, different linear (i.e., Wilcoxon test and statistical approaches) and nonlinear (Genetic algorithm [GA]) modifications for calibration of the DRASTIC framework using nitrate (NO₃ ) concentrations were compared through the preparation of groundwater vulnerability maps of the Meshqin-Shahr plain, Iran. Twenty-two groundwater samples were collected from wells in the study area, and their respective NO₃ concentrations were used to modify the ratings and weights of the DRASTIC parameters. The areas found to have the highest vulnerability were in the eastern, central, and western regions of the plain. Results showed that the modified DRASTIC frameworks performed well, compared to the unmodified DRASTIC. When measured NO₃ concentrations were correlated with the vulnerability indices produced by each method, the unmodified DRASTIC method performed most poorly, and the Wilcoxon-GA-DRASTIC method proved optimal. Compared to the unmodified DRASTIC method with an R² of 0.22, the Wilcoxon-GA-DRASTIC obtained a maximum R² value of 0.78. Modification of DRASTIC parameter ratings was found to be more efficient than the modification of the weights in establishing an accurately calibrated DRASTIC framework. However, modification of parameter ratings and weights together increased the R² value to the highest degree.

Influence of Agricultural Irrigation Activity on the Potential Risk of Groundwater Pollution: A Study with Drastic Method in a Semi-Arid Agricultural Region of China

Agricultural irrigation strongly affects groundwater pollution in cultivated areas. Groundwater vulnerability was evaluated using the DRASTIC method by considering agricultural activities that affect water infiltration and pollutant transport to the groundwater. Three scenarios, using different water recharge sources and calculation methods, were considered for the Tongliao area of northern China. For Scenario 1, only precipitation contributed to the net recharge estimation and ~33.77% of the area was under high pollution risk. For Scenarios 2 and 3, both precipitation and irrigation return water were considered for net recharge estimations. The fractional areas of high pollution risk regions were 40.60% and 19.22% for Scenarios 2 and 3, respectively. The modified infiltration coefficients for this study area were used in Scenario 3, and the fractional area of the high-risk region was 21.38% lower than for Scenario 2. The use of empirical infiltration coefficients in Scenario 2 overestimated the water infiltration ability in the cultivated areas, which also overestimated the fractional area of high-risk regions in this study. Accurate assessment of the impact of agricultural activities on the groundwater pollution risk is essential for cultivated areas. Emphasis should be placed on the calculation method of proper parameters for DRASTIC model construction.

Modified Index-Overlay Method to Assess Spatial–Temporal Variations of Groundwater Vulnerability and Groundwater Contamination Risk in Areas with Variable Activities of Agriculture Developments

The groundwater vulnerability (GV) assessment for contamination is an effective technique for the planning, policy, and decision-making, as well as for sustainable groundwater resource protection and management. The GV depends strongly on local hydrogeological settings and land-use conditions that may vary in response to the activities of agricultural development. In this study, a modified DRASTIC model, which employs an additional factor of land use coupled with the analytic hierarchy process (AHP) theory, was used to quantify the spatial and temporal variation of GV and groundwater contamination risk in the Pingtung groundwater basin. The results show that the GV slightly decreased due to the decrease in agricultural areas under the change of land use over two decades (1995–2017). The yearly changes or a shorter period of observations incorporated with the accurate land-use map in DRASTIC parameters could improve GV maps to obtain a better representation of site-specific conditions. Meanwhile, the maps of yearly contamination risk indicated that the counties of Jiuru and Ligang are at high risk of nitrate pollution since 2016. In other agriculture-dominated regions such as Yanpu, Changzhi, and Gaoshu in the Pingtung groundwater basin, the climate conditions influence less the temporal variations of groundwater contamination risk. The results of this study are expected to support policy-makers to adopt the strategies of sustainable development for groundwater resources in local areas.

Estimates of aquifer geo-hydraulic and vulnerability characteristics of Imo State and environs, Southeastern Nigeria, using electrical conductivity data

Two hundred and twenty-six vertical electrical sounding (VES) data were acquired across the study area that has six geologic formations for the purpose of evaluating the geo-hydraulic potentials and the protective capacity of the aquifers of the study area. Schlumberger array was adopted for data acquisition using the ABEM™ Terrameter SAS 4000. Results of the study revealed four to six geo-electric layers. A variety of geo-electric curve types were identified in the study area with the KK curve type being dominant. The aquifer zones lie between the third and sixth layers with their resistivity values ranging from 101 to 8900 Ωm with a mean value of 1799 Ωm. Estimates of the aquifer hydraulic characteristics using the new set of model equations based on conductivity data revealed hydraulic conductivity range of 0.925 and 13.42 m/day while transmissivity ranged between 16.0 and 887 m²/day. These findings showed that groundwater potential is high in Benin Formation, moderate in Nsukka and Ajali Formations, and generally poor within Ogwashi and Imo Shale Formations. Aquifer vulnerability studies revealed that the values of the integrated electrical conductivity (IEC) of the study area ranged between 28.4 and 2202 mS with a mean value of 403 mS. Results of the IEC revealed that the aquifer protective capacity of most parts of the study area were extremely poor (86.2%) with percolation period of several months while only 1.8% of the study area are fairly good. The aquifers of the study area may therefore be vulnerable to contamination from anthropogenic sources, and adequate aquifer protective strategies are therefore recommended.