Modified-DRASTIC, modified-SINTACS and SI methods for groundwater vulnerability assessment in the southern Tehran aquifer

Human health risk of nitrate in groundwater of Tehran-Karaj plain, Iran

Groundwater pollution by nitrate has is a major concern in the Tehran-Karaj aquifer, Iran, where the wells provide up to 80% of the water supply for a population of more than 18 million-yet detailed human health risks associated with nitrate are unknown due to the lack of accessible data to adequately cover the aquifer in both place and time. Here, using a rich dataset measured annually in more than 75 wells, we mapped the non-carcinogenic risk of nitrate in the aquifer between 2007 and 2018, a window with the most extensive anthropogenic activities in this region. Nitrate concentration varied from ~ 6 to ~ 150 mg/L, around three times greater than the standard level for drinking use, i.e. 50 mg/L. Samples with a non-carcinogenic risk of nitrate, which mainly located in the eastern parts of the study region, threatened children's health, the most vulnerable age group, in almost all of the years during the study period. Our findings revealed that the number of samples with a positive risk of nitrate for adults decreased in the aquifer from 2007 (17 wells) to 2018 (6 wells). Although we hypothesized that unsustainable agricultural practices, the growing population, and increased industrial activities could have increased the nitrate level in the Tehran-Karaj aquifer, improved sanitation infrastructures helped to prevent the intensification of nitrate pollution in the aquifer during the study period. Our compilation of annually mapped non-carcinogenic risks of nitrate is beneficial for local authorities to understand the high-risk zones in the aquifer and for the formulation of policy actions to protect the human health of people who use groundwater for drinking and other purposes in this densely populated region.

Multi-variable approach to groundwater vulnerability elucidation: A risk-based multi-objective optimization model

Groundwater vulnerability mapping is essential in environmental management since there is an increase in contamination caused by excessive population growth. However, to our knowledge, there is rare research dedicated to optimizing the groundwater vulnerability models, considering risk conditions, using a robust multi-objective optimization algorithm coupled with a multi-criteria decision-making model (MCDM). This study filled this knowledge gap by developing an innovative hybrid risk-based multi-objective optimization model using three distinguished models. The first model generated two series of scenarios for rate modifications associated with two common contaminations, Nitrate and Sulfate, based on susceptibility index (SI) and DRASTICA models. The second model was a multi-objective optimization framework using non-dominated sorting genetic algorithms- II and III (NSGA-II and NSGA-III), considering uncertainties in the input rates by the conditional value-at-risk (CVaR) technique. Finally, the third model was a well-known MCDM model, the COmplex PRoportional ASsessment (COPRAS), which identified the best compromise solution among Pareto-optimal solutions for weights of the contaminations. Regarding the Sulfate's results, although the optimized DRASTICA model led to the same correlation as the initial model, 0.7, the optimized SI model increased the correlation to 0.8 compared to the initial model as 0.58. For the Nitrate, both the optimized SI and the optimized DRASTICA models raised the correlation to 0.6 and 0.7 compared to the initial model with a correlation value of 0.36, respectively. Hence, the best and the lowest correlation among the optimized models were between SI and Sulfate concentration and SI and Nitrate concentration, respectively.

Effects of elevated arsenic and nitrate concentrations on groundwater resources in deltaic region of Sundarban Ramsar site, Indo-Bangladesh region

An attempt has been adopted to predict the As and NO₃^- concentration in groundwater (GW) in fast-growing coastal Ramsar region in eastern India. This study is focused to evaluate the As and NO₃^- vulnerable areas of coastal belts of the Indo-Bangladesh Ramsar site a hydro-geostrategic region of the world by using advanced ensemble ML techniques including NB-RF, NB-SVM and NB-Bagging. A total of 199 samples were collected from the entire study area for utilizing the 12 GWQ conditioning factors. The predicted results are certified that NB-Bagging the most suitable and preferable model in this current research. The vulnerability of As and NO₃^- concentration shows that most of the areas are highly vulnerable to As and low to moderately vulnerable to NO₃. The reliable findings of this present study will help the management authorities and policymakers in taking preventive measures in reducing the vulnerability of water resources and corresponding health risks.

Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques

Totko river basin is a semi-arid watershed, which undergoes severe water crisis during the dry season. Presently, due to increase in population, demand of food has increased leading to a rise in growth of high yield crop variety and usage of chemical fertilizers and pesticides. So, surface water as well as groundwater is getting polluted. In this study assessment of groundwater vulnerability of Totko river basin has been done using DRASTIC and Analytic Hierarchy Process (AHP) models. For this, seven hydrogeological parameters have been considered which are; Depth to water level (D), Net Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of vadose zone (I) and Hydraulic Conductivity (C). Weight and rating analysis of the seven criteria and their sub-criteria have been done using generic DRASTIC algorithm and AHP comparison matrix. Ground Water Vulnerability Map (GWV) obtained from DRASTIC and AHP analysis has been divided into five vulnerable classes. Area of very high vulnerable zone is 6.53% more in AHP based vulnerability as compared to Generic DRASTIC. Similarly, these regions show a high nitrate concentration (30-50 ppm) in groundwater. GWV maps have been validated through nitrate concentration and the accuracy of the models have been assessed through Pearson's correlation coefficient and Kappa coefficient. To prevent groundwater contamination proper land use planning and watershed management are necessary, for which vulnerable zones need to be demarcated and DRASTIC is a useful model for vulnerability assessment.

Assessment of groundwater vulnerability in coastal zone using SI method and GIS: case study of Bouficha aquifer (northeast Tunisia)

Nowadays, groundwater is under stress due to contamination, over-exploitation, seawater intrusion, climate change, etc. The groundwater contamination is the major problem which can engender the total deterioration of the aquifer. The groundwater vulnerability assessment may contribute to predicate and to delimitate the areas affected by contamination or any future pollution. This research aims to zoning the potential pollution of the Bouficha shallow aquifer, located in the northeast Tunisia, using the SI model and GIS. Five parameters are presented in the SI model: depth to groundwater (D), recharge (R), aquifer media (A), topography (T), and land use (LU). The different parameters were collected from diverse sources for assess groundwater vulnerability. The net recharge map was generated using GIS-based multi-criteria analysis method based on different parameters (slope, lithology, LU, soil, and drainage density). The generated vulnerability map shows three vulnerability classes: low vulnerability (< 45), moderate vulnerability (45-64), and high vulnerability (64-84) which represent 3.14%, 76.8%, and 20.06% of the total area, respectively. The SI vulnerability represent a moderate positive correlation with the measured nitrate concentrations (R² = 0.76). The sensitivity analysis shows that the land use parameter is the most influential parameter for groundwater vulnerability in BFC.

Assessment of groundwater vulnerability in an urban area: a comparative study based on DRASTIC, EBF, and LR models

The groundwater vulnerability assessment is known as a useful tool for predicting and prevention of groundwater pollution. This study targets the DRASTIC, evidential belief function (EBF), and logistic regression (LR) models to assess vulnerability in Kabul aquifers, Afghanistan Country. The growth of urban sprawl, groundwater overexploitation, and lack of suitable municipal sewage systems as anthropogenic sources have been the main potential to increase groundwater contaminants such as nitrate in the study area. The vulnerability map has been developed based on various effective factors including altitude, slope (percentage rise), aspect, curvature, land-use type, drainage density, distance from river, annual mean precipitation, net recharge, geology/lithology units, the impact of the vadose zone, aquifer media, depth to water (unsaturated zone), saturated zone, drawdown, and hydraulic conductivity. To identify groundwater pollution, the spatial variation of nitrate concentration data in 2018 was considered indication of groundwater pollution. Based on descriptive statistics, the value of 2.65 mg/l (the median of the pixel values of nitrate map) was selected as a threshold to differentiate the occurrence and non-occurrence of pollution. The groundwater quality data were selected and randomly divided into two datasets for training and validation, including 70% and 30%, respectively. The success-rate and prediction-rate curves were computed based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) to estimate the efficiency of models. The ROC-AUC of success rates for EBF, LR, and DRASTIC models were estimated to be 67%, 66%, and 52%, respectively. Moreover, the ROC-AUC of the prediction rates of the EBF, LR, and DRASTIC models were obtained 61%, 63%, and 55%, respectively. Based on correlation between mean nitrate concentration and the mean vulnerability indexes in each model, the EBF model is the most compatible with the current developed vulnerability zones as the role of mankind in changing the environment in real conditions in comparison to LR and DRASTIC models.

Modelling hydrogeological parameters to assess groundwater pollution and vulnerability in Kashan aquifer: Novel calibration-validation of multivariate statistical methods and human health risk considerations

Modeling and Investigation on pollution potential of aquifers is a matter of importance in terms of management, development and land-use allocation as well as quality monitoring, pollution prevention and groundwater protection. The purpose of this study is to calibrate and modeling the methods used for pollution potential assessment, in which the impact and apportionment of hydrogeological parameters on groundwater pollution of an aquifer located in Kashan is considered. To do so, Analytic Hierarchy Process (AHP) and fuzzy-statistical analysis methods are used for weighting, ranking and standardize the parameters based on research awards of experts and Ad-Hoc systems. This was performed in such a way that the level and importance of each class of classification parameters is considered equal to the final model, and is equivalent to the reclassified class of indices of groundwater quality and human health risk to nitrate pollution. After ranking and standardizing the parameters as well as final model by using fuzzy-statistical approach, the process of weighting the parameters is accomplished with aid of AHP and Factor Analysis-weighted Principal Component Analysis (FA-PCA) methods based on their apportion and impact on groundwater pollution in addition to their correlation with nitrate map. In addition to the correlation with the standardized nitrate concentration, techniques of the root mean square error (RMSE) and coefficient of variation (COV) are employed to validate the model. The results illustrated that parameters of net recharge, soil media, impact of vadose zone, hydraulic conductivity and aquifer media have created the highest apportion and impact on groundwater pollution. In addition, it was found that weight of these parameters for calibrated and validated model of GPPI (groundwater pollution potential index) is proved to be 8.5, 3.4, 3.3, 2.6, 2.2, for GPRI (groundwater pollution risk index) as the best model is 4.4, 3.7, 3.1, 2.9, 1.1, and it is 4.8 for the land use layer, respectively. Weighting procedure was conducted by FA-PCA approach and following considerations were used; R = 73, RMSE = 1.08 and COV = 20%. Moreover, based on these models with better calibration-validation than generic model, it was found high pollution potential in western margin, high pollution risk in the central parts to the western margin, while it was observed not to have that very high pollution potential and risk in Kashan aquifer.

Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms

Groundwater management is essential in water and environmental engineering from both quantity and quality aspects due to the growing urban population. Groundwater vulnerability evaluation models play a prominent role in groundwater resource management, such as the DRASTIC model that has been used successfully in numerous areas. Several studies have focused on improving this model by changing the initial parameters or the rates and weights. The presented study investigated results produced by the DRASTIC model by simultaneously exerting both modifications. For this purpose, two land use-based DRASTIC-derived models, DRASTICA and susceptibility index (SI), were implemented in the Shiraz plain, Iran, a semi-arid region and the primary resource of groundwater currently struggling with groundwater pollution. To develop the novel proposed framework for the progressive improvement of the mentioned rating-based techniques, three main calculation steps for rates and weights are presented: (1) original rates and weights; (2) modified rates by Wilcoxon tests and original weights; and (3) adjusted rates and optimized weights using the genetic algorithm (GA) and particle swarm optimization (PSO) algorithms. To validate the results of this framework applied to the case study, the concentrations of three contamination pollutants, NO₃, SO₄, and toxic metals, were considered. The results indicated that the DRASTICA model yielded more accurate contamination concentrations for vulnerability evaluations than the SI model. Moreover, both models initially displayed well-matched results for the SO₄ concentrations, specifically 0.7 for DRASTICA and 0.58 for SI, respectively. Comparatively, the DRASTICA model showed a higher correlation with NO₃ concentrations (0.8) than the SI model (0.6) through improved steps. Furthermore, although both original models demonstrated less correlation with toxic metal concentrations (0.05) compared to SO₄ and NO₃ concentrations, the DRASTICA and SI models with modified rates and optimized weights exhibited enhanced correlation with toxic metals of about 0.7 and 0.2, respectively.

Assessment of groundwater vulnerability using remote sensing, susceptibility index, and WetSpass model in an arid region (Biskra, SE Algeria)

Biskra region currently shows signs of stress and a high risk of groundwater contamination by various chemicals and pesticides. For this purpose, a modified integrated susceptibility index (SI) is coupled with remote sensing (RS) and WetSpass model to assess the sensitivity of the groundwater and the risk of pollution in the most exploited aquifer (Quaternary aquifer) in the study area. The results of the modified SI model show that a major part of the aquifer is at risk of contamination if the farmers do not implement good agricultural practices. Four sensitivity levels are considered, reflecting a vulnerability rating that ranges from low to very high. The very high category is observed in the agricultural areas with an estimated pollution index ranging from 84 to 90.57, while a large part of the aquifer shows a high vulnerability to contamination (64 < SI ≤ 84). This category is found in areas characterized by the dominance of bare soil. In urban areas, the vulnerability level decreases to low category (37 < SI ≤ 45). However, the area of forests is classified as moderate to vulnerability (45 < SI ≤ 64). The different statistical and GIS methods confirm the reliability of the obtained SI map. The combination of the SI method with WetSpass model and RS can give a reliable map to help and assist the authorities and decision-makers in groundwater resources planning and the implementation of monitoring programs and networks to control the quality of groundwater in arid environments.

Groundwater Vulnerability Assessment in the Metaponto Coastal Plain (Basilicata, Italy)

This study aims at a groundwater vulnerability assessment of the Metaponto coastal plain, located in the Basilicata region (southern Italy). In the last century, intensive agriculture, zootechnical and industrial activities have significantly changed the plain. These changes led to negative impacts on the hydrogeological system intensifying the risk of the aquifer to pollution. The paper presents the assessment of the intrinsic vulnerability of the coastal aquifer carried out by the GIS-based application of the SINTACS method. It considers several aquifer parameters such as water table depth, effective infiltration, unsaturated conditions, soil media, aquifer media, hydraulic conductivity and topography. Furthermore, the anthropogenic influence in the study area was considered by applying the SINTACS-LU method, in which the parameter of land use (LU) was added. The SINTACS and SINTACS-LU vulnerability indexes were provided by summing the product of ratings and weights assigned to each parameter. The analysis of the intrinsic vulnerability map allowed for determining three classes ranging from low to high vulnerability. In both cases, the southeastern part of the coastal plain, closest to the sea, shows the highest vulnerability class, indicating that it is the most vulnerable to contamination due to the hydrogeological intrinsic factors. The wide central part of the study area shows a moderate class of vulnerability and the low class is scattered in small parts in the northern portion of the plain, which represents the areas less contaminable in space and time in the case of potential pollution. In the SINTACS-LU map, some areas classified as highly vulnerable in the SINTACS method show a minor vulnerability class. These areas are localized in natural and wooded sectors of the Metaponto plain, which are less populated, where human impact on the groundwater is minimal.

Vulnerability mapping of the Paravanar sub-basin aquifer (Tamil Nadu, India) in SINTACS model for efficient land use planning

Consideration of groundwater vulnerability as a planning parameter is imperative in the current context of depleting groundwater resources for the efficient land use planning. This study aims for groundwater vulnerability assessment by modifying SINTACS model and involve dynamics of land use change in a case study of Paravanar sub-basin in the Tamil Nadu state of south India. Thematic maps of land use generated from remote sensing data and associated field investigations were the input for the SINTACS model. These maps integrated in GIS helped to derive intrinsic vulnerability into very low, low, medium and high vulnerability categories. The strongest correlation (r = 0.74) between intrinsic vulnerability index and the water quality index, estimated from field observations, suggested better efficiency of this model compared to the conventional SINTACS index. Application of the modified SINTACS led to the conclusion that 12.2%, 28.7%, 45.9%, and 13.1% of the study area categorized very low vulnerability, low vulnerability, moderate vulnerability and high vulnerability, respectively and should be considered for efficient land use planning.

Assessment of Groundwater Contamination Risk in Oilfield Drilling Sites Based on Groundwater Vulnerability, Pollution Source Hazard, and Groundwater Value Function in Yitong County

Oilfield drilling sites are the potential dispersive pollution source of groundwater, especially to shallow groundwater. The pollution risk assessment in these areas is an important reference for effective groundwater management and protection. The vulnerability assessment alone is not sufficient for groundwater contamination risk assessment. In this study, we developed a comprehensive groundwater pollution risk assessment method for oilfield drilling sites that combine groundwater vulnerability, pollution source hazard, and groundwater value function to produce a more comprehensive result. Consider the oilfield drilling area in Yitong County of Jilin Province, China, as an example. Thematic maps of the three aspects (groundwater vulnerability, pollution source hazard, and groundwater value function) were generated in ArcGIS environment to assess the contamination risk of groundwater in quaternary pore unconfined aquifer. The results show that 9.92% of the study area is characterized as being at high risk. These areas are mainly distributed around the center position of the oil drilling site, floodplains, and the reservoir. The moderate risk area accounts for 21.04% of the total area. It is distributed in the first-level terrace, mainly because of the high function value of groundwater. The remaining 69.04% of the study area is characterized as none and mild risk, mainly distributed in the valleys and terraces. This integrated groundwater contamination risk assessment method is suited for comparative assessment of multiple-point sources of contamination at a regional scale. Finally, the groundwater contamination risk grade distributed in this area provides a reference for effective protection and sustainable supply of groundwater in the oilfield drilling area.

Nitrate vulnerability of groundwater in Jeju Volcanic Island, Korea

Groundwater is the sole source of water for about 670,000 residents of Jeju Island, which is a volcanic Korean island. Since the 1990s, nitrate contamination of groundwater has emerged as a major environmental issue. To ensure the sustainability of water resources, this study aimed to develop a vulnerability model for nitrate contamination as a preventive measure. Based on intrinsic vulnerability determined using the DRASTIC model, the effects of anthropogenic parameters related to NO₃ sources and groundwater use (land use and the hydraulic gradient, respectively) on contamination were tested using a geographic information system (GIS). The correlation between groundwater nitrate distribution and vulnerability was considerably stronger compared to the DRASTIC method, with the correlation coefficients (r) increasing from -0.048 to 0.562 and -0.069 to 0.481 in the western and eastern regions, respectively. However, in the southern and northern regions, nitrate concentrations in groundwater are low, likely due to the heavily paved land surface that resulted from urbanisation, such that groundwater vulnerability appeared negligible. To prevent further nitrate contamination in coastal groundwater, management policies for land use and groundwater exploitation should be enacted along with continuous groundwater monitoring at the regional scale.

Dilution of PAHs loadings of particulate matter in air, dust and rivers in urban areas: A comparative study (Tehran megacity, Iran and city of Tübingen, SW-Germany)

PAHs (polycyclic aromatic hydrocarbons) in urban areas are usually bound to particles. Concentrations are different in different compartments (airborne particles, street dust, suspended sediments in rivers and channels). This study follows concentrations of PAHs from particles in air to street dust and finally suspended sediments in the city of Tehran, Iran compared to Tübingen, Germany. Data sets are based on own investigations (PAHs on suspended sediments), or taken from literature studies (PAHs in street dust and airborne particles). Based on a cross-comparison of concentrations of PAHs on particles, and their congener distribution patterns, the occurrence, interrelation (exchange and mixing processes), as well as possible dilution processes among PAHs in the different particle classes are disentangled. Results show that for Tehran and Tübingen PAHs in airborne particles are very high (in the range of 500 mg kg^-1). However, in street dust and suspended sediments PAHs concentrations on particles are around 100 times lower. Surprisingly concentrations in street dust and suspended sediments are 5 to 10 times lower in Tehran (average 0.5 mg kg^-1) than in Tübingen (average 5 mg kg^-1). Since it is unlikely that PAHs emissions are lower in the Tehran megacity, an effective dilution of the atmospheric signal by uncontaminated (background) particles is hypothesized. Uncontaminated particles may stem from wind erosion of bare surfaces, construction and sand mining sites or even dust from the desert areas, which are frequent in arid climate in Tehran.

New DRASTIC framework for groundwater vulnerability assessment: bivariate and multi-criteria decision-making approach coupled with metaheuristic algorithm

Unplanned anthropogenic activities and erratic climate events pose serious threats to groundwater contamination. Therefore, the vulnerability assessment model becomes an essential tool for proper planning and protection of this precious resource. DRASTIC is an extensively adopted groundwater vulnerability assessment model that suffers from several shortcomings in its assessment due to the subjectivity of its rates and weights. In this paper, a new framework was developed to address the subjectivity of DRASTIC model using a bivariate, multi-criteria decision-making approach coupled with a metaheuristic algorithm. Shannon entropy (SE) and stepwise weight assessment ratio analysis (SWARA) methods were coupled with biogeography-based optimization (BBO) to modify rates and weights. The performance of developed models was assessed using area under the receiver operating characteristic (AU-ROC) curve and weighted F1 score. The Shannon-MH model yields better results with an AUC value of 0.8249, whereas other models resulted in an AUC value of 0.8186, 0.7714, 0.7672, and 0.7378 for SWARA-MH, SWARA, SE, and original DRASTIC models, respectively. It is also evident from weighted F1 score that Shannon-MH model produced maximum accuracy with a value of 0.452 followed by 0.437, 0.419, 0.370, and 0.234 for SWARA-MH, SWARA, SE, and original DRASTIC models, respectively. The results indicated that Shannon model coupled with metaheuristic algorithm outperforms other developed models in groundwater vulnerability assessment.

A GIS-based approach for geospatial modeling of groundwater vulnerability and pollution risk mapping in Bou-Areg and Gareb aquifers, northeastern Morocco

Groundwater resources are the main supply of freshwater for human activities. Nevertheless, during the last 50 years, groundwater has become very susceptible to chemical pollution due to human activities. The groundwater vulnerability assessment constitutes a worldwide recognized tool for water management and protection. In this study, the GIS-based DRASTIC and pollution risk models have been used to assess the intrinsic vulnerability and risk to pollution of the Gareb and Bou-Areg aquifers, the main irrigated areas in the northeast of Morocco, by analyzing available hydrogeological attributes. The seven hydrogeologic factors used to assess vulnerability were depth to aquifer, net recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity, while an eighth parameter has been added to assess the pollution risk which is the land use. The resultant vulnerability map reveals that about 0.06% of the study area is in low vulnerability zones, 83.68% is moderately vulnerable, and 16.26% is highly vulnerable to groundwater pollution. The results also reveal that groundwater is highly vulnerable in the Gareb aquifer and the coastal zone, where the water table is very low, the slope is gentle, and the geological formations are permeable. In addition, moderate to low vulnerability is found towards the west of the study area where the groundwater is located in deep aquifers. The groundwater pollution risk map is obtained by overlaying the land use with the DRASTIC vulnerability. The central and western parts of Bou-Areg as well as the south of Gareb are dominated by high and very high pollution risk classes, and present 43.07% of the study area, which is strongly influenced by urban areas, agricultural activities, and shallow groundwater systems. 30.11% of the surface is moderately vulnerable, mainly in areas where human activity is not widely observed, while the very low and low pollution risk classes represent a total of 26.82% of the total area. The mapping models were validated using nitrate concentration and electrical conductivity data in groundwater as an indicator of pollution. A positive correlation was observed when validating these models. The resultant groundwater vulnerability and pollution risk maps might provide an early warning to policy maker and manager to manage and avoid further stress on this invaluable resource.

Groundwater vulnerability assessment using GIS-based DRASTIC model in Nangasai River Basin, India with special emphasis on agricultural contamination

Nangasai basin is a semi-arid watershed where agriculture is the main source of economy. In present day, increasing population demands increase in food productivity which leads to increase use of fertilizers and chemical pesticides in agriculture. These fertilizers on the other hand mix up with the groundwater and increase the pollution, which affects human health adversely. So, for controlling the groundwater contamination risk proper water resource management and assessment of groundwater vulnerability is extremely important. Total 7 hydrogeological parameters have been considered for this study, and the final groundwater vulnerability map has been prepared by overlay weighted method with the help of DRASTIC index, which is classified into 5 vulnerable classes (very high, high, moderate, low, and very low). In the south and south-eastern regions of the basin namely Deghi, Bankada, Baram, Macha, Katin, Tilabani high groundwater contamination is been observed. For validating the model, the water quality parameters-nitrate and TDS have been used with the accuracy of 89% and 86% respectively. Using effective as well as scientifically approved methods, the anthropogenic and agricultural contamination can be controlled and managed which will lower the risk of contamination. This map can be further utilized as a base map for management of groundwater pollution and its planning.

Developing a SINTACS-based method to map groundwater multi-pollutant vulnerability using evolutionary algorithms

In this study, the modified SINTACS method, a rating-based groundwater vulnerability approach, was applied to data from the Campanian Plain, southern Italy, to identify groundwater vulnerable areas accurately. To mitigate the subjectivity of SINTACS rating and weighting schemes, a modified SINTACS model was formulated by optimizing parameter ratings using the Wilcoxon rank-sum test, and the weight scores using the evolutionary algorithms including artificial bee colony (ABC) and genetic algorithm (GA) methods. The validity of the models was verified by analyzing the correlation coefficient between the vulnerability index and nitrate (NO₃) and sulfate (SO₄) concentrations found in the groundwater. The correlation coefficients between the pollutant concentrations and the relevant vulnerability index increased significantly from - 0.35 to 0.43 for NO₃ and from - 0.28 to 0.33 for SO₄ after modifying the ratings and weights of typical SINTACS. Besides, a multi-pollutant vulnerability map considering both NO₃ and SO₄ pollutants was produced by amalgamating the best calibrated vulnerability maps based on the obtained correlation values (i.e., the Wilcoxon-ABC-based SINTACS vulnerability map for NO₃ and the Wilcoxon-GA-based SINTACS vulnerability map for SO₄). The resultant multi-pollutant vulnerability map coincided significantly with a land use map of the study area, where anthropogenic activities represented the main sources of pollution.

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.

Assessing the Groundwater Quality in the Liwa Area, the United Arab Emirates

Last period groundwater quality raises big concerns all over the world since it is a limited source of drinkable water and for agricultural and industrial use. While the suitability of the groundwater of Liwa aquifer (Abu Dhabi Emirate) for agricultural use has been previously partially studied, not all the water parameters have been taken into account. Therefore, in this paper, we propose the study of 42 concentrations series of 19 groundwater parameters. We test the hypothesis that the water parameters series recorded at different locations are similar and group the samples in clusters. The main parameters that determine the differences between the clusters are determined by Principal Component Analysis (PCA). Finally, we use a quality index for assessing the water suitability for drinking. The conclusions emphasize the necessity of using more than one technique to evaluate water quality for different purposes and to cross-validate the results.

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.