Search

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.

Geo-electrical survey was conducted in a highly industrialized area to delineate the freshwater and saline water aquifers. A total of 30 vertical electrical soundings (VES) were made along the coastal aquifers of Tuticorin, which covers both sedimentary formation and crystalline rocks. By using VES data, GIS was used to create spatial maps for resistivity and thickness at various depths. The results show that Q and H were the dominant curve types in the study area. Q type curves indicate saline water by decreasing resistivity values with respect to depths. In H type curves, low resistivity saline water aquifer was sandwiched between high resistivity topsoil and hard rock at the deeper horizon. The geophysical indicators such as Dar-Zarrouk parameters were calculated using the VES results. The Longitudinal unit conductance (S) values ranged between 0.075 and 7500 S. The transverse unit resistance (T) of the study area varied from 16.06 to 5909.25 Ωm2. The anisotropy (λ) values ranged from 1.00 to 55. Interpretation of data reveals that the saline water intrusion and industrial impact on shallow aquifers were observed in the coastal region of the study area. Few pockets of the freshwater aquifer were also noted in deeper horizons. Since the quality of groundwater was deteriorating, proper management plans will be needed to save this fragile coastal aquifer.

Groundwater is the major freshwater resource in urban and rural areas of India that provides potable water. The quality evaluation of existing groundwater resources is vital and it's quantity for the optimal utilization and maintenance. The bounding coordinates of the selected study area of Tuticorin industrial area is between 8°38'24" and 8°51'0" latitude and between 77°54'36" and 78°12'36" longitude. Groundwater samples were collected as grid form at 40 locations during the pre- and postmonsoon seasons in the year 2017. Fe, Zn, Co, Pb, Mn, Ni, Cr, and Cu metal concentrations were determined using AAS (Atomic Absorption Spectrophotometer)-Perkin Elmer makes the model AAnalyst 200. Most of the groundwater samples were exceeded by the WHO 2008; USEPA 2009; and BIS 2012 guideline for drinking water standards. Further to assess the groundwater pollution status based on the heavy metal indices such as heavy metal pollution index (HPI), heavy metal evaluation index (HEI), degree of contamination (DOC), hazard quotient (HQ), hazard index (HI). Statistical analyses to found the appropriateness of groundwater for consumption and factors of contamination. The evaluation results indicate that groundwater is highly deteriorated and unsuitable for drinking in premonsoon period. While evaporation of water which increases the heavy metal concentration in premonsoon and dilution factor was affected in postmonsoon season. The increased concentration of heavy metals in groundwater might have been caused by evaporation, anthropogenic activities, and dissolution of rock formations which poses risk to human health. If this kind of growing contamination in the groundwater is unattended, it may lead to various health issues to the people from this region. Therefore, a consistent and sustainable water management should be carried out in this region in order to improve the groundwater quality.

This study is to assess the hydrogeochemical characteristics of groundwater at the deltaic region of the Nakdong River Basin in the Busan Metropolitan City of Korea. The study area is covered by the Quaternary sedimentary deposits and the Cretaceous granites associated with unconformity. The thick sedimentary deposits consists of two aquifers, i.e., unconfined and confined aquifers on the basis of clay deposit. Groundwater samples were collected from seven boreholes: two from unconfined aquifer and five from confined aquifer systems during the wet season of 2017 year. ORP and DO indicates that the groundwater of the unconfined aquifer exists in the oxidization condition and that of the confined aquifer pertains in the reduction condition. Piper’s trilinear diagram shows CaSO4 type for groundwater of the unconfined aquifer, and NaCl type for that of the confined aquifer. Ionic concentrations of groundwater increase in the confined aquifer because of direct and reverse ion exchange processes. Carbonate weathering and evaporation are other mechanisms in the water-rock interaction. Saturation indices of dolomite and calcite are observed as oversaturated, while halite reveals undersaturation. Hierarchical cluster analysis (HCA) exhibits that cluster 1 and cluster 2 represents the properties of groundwater in unconfined and confined aquifers, respectively. Factor analysis shows that groundwater of the confined aquifer is much influenced by seawater, and includes heavy metals of iron and aluminum. Groundwater samples in unconfined and confined aquifers are located at the rock weathering and evaporation zones in the Gibbs diagram. Inverse geochemical modeling of PHREEQC code suggests that carbonate dissolution and ion exchange of major ions are the prevailing geochemical processes. This comprehensive research provides the distinguished hydrogeochemical characteristics of groundwater in confined and unconfined aquifer systems of the Nakdong River Basin in Busan City, Korea.

Submarine groundwater discharge (SGD) is the groundwater flow from land to the sea across the seabed, and it includes both terrane freshwater and recirculated seawater in the sub-surface. This review (i) systematically evaluates findings of various quantification methodologies, (ii) examines the estimated SGD in scientific publications between 2000 and 2020, and (iii) quantitatively evaluates current situation of coastal zone management through the bibliometric analysis of research papers. Apart from enhancing the shortage of groundwater resources in coastal area, the SGD brings nutrients (nitrate and phosphate), toxic heavy metals, and organic compounds, and thus contaminate the seawater. Therefore, the improved understanding about location and quantity of global SGD is essential to conserve the coastal and ocean ecosystems.

The accurate evaluation of groundwater contamination vulnerability is essential for the management and prevention of groundwater contamination in the watershed. In this study, advanced multiple machine learning (ML) models of Radial Basis Neural Networks (RBNN), Support Vector Regression (SVR), and ensemble Random Forest Regression (RFR) were applied to determine the most accurate performance for the evaluation of groundwater contamination vulnerability. Eight vulnerability factors of DRASTIC-L were rated based on the modified DRASTIC model (MDM) and were used as input data. The adjusted vulnerability index (AVI) with nitrate values was used as output data for the modeling process. The performance of three models was verified using the statistical performance criteria of MAE, RMSE, r2, and ROC/AUC values. The ensemble RFR model showed the highest performance in comparison with standalone SVR and RBNN models. Specifically, ensemble RFR kept all promising solutions during the model performance due to its flexibility and robustness, and the vulnerability map obtained by the RFR model was more accurate for predicting the most vulnerable areas to contamination. It was concluded that ensemble RFR was a robust tool to enhance the evaluation of groundwater contamination vulnerability, and that it could contribute to environmental safety against groundwater contamination.

Groundwater decrease and quality deterioration are common phenomena at coastal areas with subway tunnels in the world. This study investigated the problems in Busan Metropolitan City of Korea, using the integrated techniques of hydrogeological, hydro-geochemical, geostatistical, multivariate statistical and isotopic analyses. Groundwater around the subway was heavily discharged, and the groundwater level around the subway was fallen to −25.3 m on basis of mean sea level. The deep drawdown of groundwater level spurred the induction of seawater and salinized river water toward the inland area, and the groundwater was contaminated around the subway. This study identified that groundwater-level largely descended due to the excessive utilization of groundwater and the severe groundwater discharge from the subway tunnels, and that seawater and salinized river water intruded the inland groundwater and contaminated the groundwater around the subway. It is considered that this study will contribute to the investigation for the causes of groundwater decrease and contamination around subway tunnels in the worldwide metropolitan cities as well as the Busan City of Korea.

The groundwater quality of Kadavanar watershed, Amaravathy sub-basin, Cauvery river basin, Tamil Nadu, India, was assessed by collecting 147 groundwater samples during April 2016 (pre-monsoon). The Kadavanar watershed area spans for about 2254.66 km2. The areal extent of the hill and forest is 397.08 km2 and the plain or the investigation area is 1857.58 km2. In the study area, sixteen parameters were found to be responsible for the degradation of groundwater quality. The integration of groundwater quality data has been carried out by considering sixteen parameters using GIS technology. The areal extent obtained from the integrated groundwater quality map reveals that nearly 54.02% of the watershed area possesses permissible category (most desirable + maximum allowable) of groundwater. The “most desirable” category of groundwater quality covers 397.08 km2 of the study area and it is located in the northern part (confluent point) as well as the high lineament and weaker plain of the watershed. The rest of the area (854.19 km2) is under mixed category of allowable and not permissible zones and extend over the watershed. It is located in central part of the watershed.

The study area, Sivagangai district is considered as one of the drought prone districts of south India. Hence, there is a need of study to identify the groundwater potential zones in this region. Firstly, thematic layers (geomorphology, geology, drainage, lineament, slope, and soil) were produced using satellite images in Arc GIS platform. Analytical hierarchy processes (AHP) was done to compute the weightage for each layer with respect to the relative importance of groundwater potential index. All the thematic layers were reclassified according to their water-bearing properties with the weightages derived by AHP. The consistency of derived weightage is evaluated as 0.082 which is below the standard consistency ratio of 0.1 and is consistent. Through overlying analysis of all thematic layers, a groundwater potential map was produced using geographic information system (GIS). Four major groundwater potential zones were identified as very good, good, moderate, and poor. Majority of the study area were classified as moderate (38.2%) and good (30.8%) groundwater potential zones. Groundwater level map was used to validate the groundwater potential zone. The groundwater potential map can be used to identify the appropriate locations for artificial recharge. Artificial recharging structures such as percolation ponds, recharge shaft, and farm ponds have to be implemented to improve the water level in the region. The outcome of this study strengthens the knowledge of geospatial analysis for groundwater vulnerability and also allows policymakers in this drought-prone area to sustainably manage water supplies.

The COVID-19 lockdown has been reported as a "ventilator" for the reinstatement of natural resources across the globe. Hence, the present study attempts to evaluate the impact of COVID-19 lockdown on the water quality of River Gomti across its stretch of ~960 km through the assessment of 'Water Quality Index' (WQI). The study also highlights the potential risk of faecal-oral transmission of COVID-19 through intake of river water facing the issue of direct discharge of domestic sewage. A deterioration in the water quality was witnessed at ~69% sampling locations during the lockdown period (May 2020). Interestingly, none of the water samples during the pre-lockdown, lockdown, and post-lockdown periods across the whole stretch belonged to the "excellent" category (WQI

We assessed groundwater pollution index (GPI) and groundwater quality of coastal aquifers from Tiruchendur in South India for drinking and irrigation by evaluating the physico-chemical parameters of 35 samples of mainly Na-Cl type in an area of 470 km2 with respect to the World Health Organization (WHO) standard as well as by estimating different indices such as total hardness (TH), sodium percentage (Na%), magnesium ratio (MR), Kelley’s ratio index (KR), potential salinity (PS), Langelier saturation index (LSI), residual sodium carbonate (RSC), sodium adsorption rate (SAR), permeability index (PI), and the irrigation water quality index (IWQI). Minimal influence of aquifer lithology and the dominant influence of evaporation on groundwater chemistry reflected the semi-arid climate of the study area. Electrical conductivity (EC) of about 89% of the samples across 418 km2 exceeded the permissible limit and Ca values of 74% of samples, however, remained within the allowable limit for drinking. More chloride was caused by influx of seawater and salt leaching and higher K was due to excessive fertilizer usage for agriculture. The spatial distribution map created using inverse distance weighting (IDW) method shows that the suitable groundwater is present close to the river basin. GPI values between 0.40 and 4.7, with an average of 1.5, classify insignificant pollution in 43% of the study region and the groundwater suitable for drinking purposes. In addition, 17% of the groundwater samples are also marginally suitable for drinking. The irrigation water quality indices provided contradictory assessments. Indices of TH, Na%, MR, PS, and LSI suggested 32–95% of the samples as unsuitable for irrigation, whereas the indices of RSC, SAR, and PI grouped 72–100% samples as permissible for irrigation. The IWQI map, however, indicated that the groundwater from more than half of the study area are not apt for irrigation and the groundwater of about one-third of the area could only be applied to salt-resistant plants.

The enhanced assessment of groundwater contamination vulnerability is necessary for the management and conservation of groundwater resources because groundwater contamination has been much increased continuously in the world by anthropogenic origin. The purpose of this study is to determine the best model among three ANFIS-MOA models (the adaptive neuro-fuzzy inference system (ANFIS) combined with metaheuristic optimization algorithms (MOAs) such as genetic algorithm (GA), differential evolution algorithm (DE) and particle swarm optimization (PSO)) in assessing groundwater contamination vulnerability at a nitrate contaminated area. The Miryang City of South Korea was selected as the study area because the nitrate contamination was widespread in the city with two functions of urban and rural activities. Eight parameters (depth to water, net recharge, topographic slope, aquifer type, impact to vadose zone, hydraulic conductivity and landuse) were classified into the numerical ratings on basis of modified DRASTIC method (MDM) for the input variables of ANFIS-MOA models. The Original ANFIS, and 3 combined models of ANFIS-PSO, ANFIS-DE and, ANFIS-GA used 95 adjusted vulnerability indices (AVI) as the target data of training (70% data) and testing (30% data) processing. The performance of 4 models was evaluated by mean absolute errors (MAE), root mean square errors (RMSE), correlation coefficients (R), ROC/AUC curves and predicted AVI (PAVI) maps. The statistical results, spatial vulnerability maps and correlation coefficients between PAVIs and nitrate concentrations revealed that the order of model excellence was ANFIS-PSO, ANFIS-DE, ANFIS-GA, and Original ANFIS, and that ANFIS-PSO showed the highest performance in training and testing processing. The performance rates of ANFIS-MOA models were also compared with 10 recent popular worldwide models using the correlation coefficients between PVI and nitrate concentrations, and they were superior to other recent popular models. ANFIS-MOA models were also useful for resolving the subjectivity of physical and hydrogeological parameters in original DRASTIC method (ODM) and MDM. It is expected that ANFIS-PSO models will produce the excellent results in assessing groundwater contamination vulnerability and that they can greatly contribute to the groundwater security in other areas of the world as well as Miryang City of South Korea.

A capability for aggregating risks to aquifers is explored in this paper for cases with sparse data exposed to anthropogenic and geogenic contaminants driven by poor/non-existent planning/regulation practices. The capability seeks 'Total Information Management' (TIM) under sparse data by studying hydrogeochemical processes, which is in contrast to Human Health Risk Assessment (HHRA) by the USEPA for using sample data and a procedure with prescribed parameters without deriving their values from site data. The methodology for TIM pools together the following five dimensions: (i) a perceptual model to collect existing knowledge-base; (ii) a conceptual model to analyse a sample of ion-concentrations to determine groundwater type, origin, and dominant processes (e.g. statistical, graphical, multivariate analysis and geological survey); (iii) risk cells to contextualise contaminants, where the paper considers nitrate, arsenic, iron and lead occurring more than three times their permissible values; (iv) 'soft modelling' to firm up information by learning from convergences and/or divergences within the conceptual model; and (v) study the processes within each risk cell through the OSPRC framework (Origins, Sources, Pathways, Receptors and Consequence). The study area comprises a series of patchy aquifers but HHRA ignores such contextual data and provides some evidence on both carcinogenic and non-carcinogenic risks to human health. The TIM capability provides a greater insight for the processes to unacceptable risks from minor ions of anthropogenic nitrate pollutions and from trace ions of arsenic, iron and lead contaminants.

Ulsan mine produced the iron ore minerals of magnetite, arsenopyrite, and scheelite in 1992, and serpentine was developed from 1977 to 2002. The soils of the mine were contaminated by heavy metals such as As, Zn, Ni, and Cd. Heavy metals of Ni and Zn came mostly from serpentinite, and As was derived mainly from arsenopyrite in the scan-type iron ore body. As, Zn, and Ni were major contaminants, but Cd was a minor contaminant on a basis of Korean standard. The heavy metals in the deep depth (> 5 m) came from the host rocks, and those in the shallow depth (