The present study deals with possible contamination of the soil by metal ions which have been affecting the environment. The concentrations of metal ions in 14 borehole samples were studied using the ICP-OES standard method. The degree of contamination was determined on the basis of single element pollution index (SEPI), combined pollution index (CPI), soil enrichment factor (SEF), and geo-accumulation index (Igeo). Geo-accumulation indices and contamination factors indicated moderate to strong contaminations for eight boreholes (BL-1, BL-2, BL-6, BL-8, BL-9, BL-10, BL-12, and BL-13) while the rest were extremely contaminated. Among all the boreholes, BL-3 and BL-11 demonstrated the highest level of Cd(II) and Pb(II) which were found the most polluted sites. The level of metal contamination was also compared with other countries. The development, variation, and limitations regarding the regulations of soil and groundwater contamination can be provided as a helpful guidance for the risk assessment of metal ions in developing countries.
The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater flowing well zones could be used to identify new wells and manage groundwater storage in a sustainable manner.
This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.
Groundwater hazard assessments involve many activities dealing with the impacts of pollution on groundwater, such as human health studies and environment modelling. Nitrate contamination is considered a hazard to human health, environment and ecosystem. In groundwater management, the hazard should be assessed before any action can be taken, particularly for groundwater pollution and water quality. Thus, pollution due to the presence of nitrate poses considerable hazard to drinking water, and excessive nutrient loads deteriorate the ecosystem. The parametric IPNOA model is one of the well-known methods used for evaluating nitrate content. However, it cannot predict the effect of soil and land use/land cover (LULC) types on calculations relying on parametric well samples. Therefore, in this study, the parametric model was trained and integrated with the multivariate data-driven model with different levels of information to assess groundwater nitrate contamination in Saladin, Iraq. The IPNOA model was developed with 185 different well samples and contributing parameters. Then, the IPNOA model was integrated with the logistic regression (LR) model to predict the nitrate contamination levels. Geographic information system techniques were also used to assess the spatial prediction of nitrate contamination. High-resolution SPOT-5 satellite images with 5 m spatial resolution were processed by object-based image analysis and support vector machine algorithm to extract LULC. Mapping of potential areas of nitrate contamination was examined using receiver operating characteristic assessment. Results indicated that the optimised LR-IPNOA model was more accurate in determining and analysing the nitrate hazard concentration than the standalone IPNOA model. This method can be easily replicated in other areas that have similar climatic condition. Therefore, stakeholders in planning and environmental decision makers could benefit immensely from the proposed method of this research, which can be potentially used for a sustainable management of urban, industrialised and agricultural sectors.
In an effort to determine the reason behind excellent nitrate remediation capacity at Kelantan region, a multivariate approach is employed to evaluate extent to which the influence of sea on soil geochemical composition affect variation pattern of groundwater quality. The results obtained from geochemical analysis of paleo-beach soil in coastal site at Bachok revealed multiple redox activity at different soil strata, involving both heterotrophic and autotrophic denitrification. In soil and water analysis, eight of the fourteen hydro-geochemical parameters (conductivity, temperature, soil texture, oxidation reduction potential, pH, total organic carbon, Fe, Cu, Mn, Cl-, SO42-, NO2-, NO3- and PO43-) measured using standard procedures were subjected to multivariate analysis. Evaluation of general variation pattern across the area reveals that the principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) are in consonance with one another on apportioning three parameters (SO42-, Cl- and conductivity) to the coastal sites and two parameters (Fe and NH4+ or NO3-) to inland sites. The step forward analysis of LDA reveals four parameters in order of decreasing significance as Cl-, Fe and SO42-, while the two-way HCA identifies three clusters on location basis, respectively. In addition to the significant data reduction obtained, the results indicate that proximity to sea and location/geological-based influence are more significant than temporal-based influence in denitrification. By extension, the research reveals that influence of labile portion of natural resources is explorable for broader application in other remediation strategies.
Ever increasing demand for water resources for different purposes makes it essential to have better understanding and knowledge about water resources. As known, groundwater resources are one of the main water resources especially in countries with arid climatic condition. Thus, this study seeks to provide groundwater potential maps (GPMs) employing new algorithms. Accordingly, this study aims to validate the performance of C5.0, random forest (RF), and multivariate adaptive regression splines (MARS) algorithms for generating GPMs in the eastern part of Mashhad Plain, Iran. For this purpose, a dataset was produced consisting of spring locations as indicator and groundwater-conditioning factors (GCFs) as input. In this research, 13 GCFs were selected including altitude, slope aspect, slope angle, plan curvature, profile curvature, topographic wetness index (TWI), slope length, distance from rivers and faults, rivers and faults density, land use, and lithology. The mentioned dataset was divided into two classes of training and validation with 70 and 30% of the springs, respectively. Then, C5.0, RF, and MARS algorithms were employed using R statistical software, and the final values were transformed into GPMs. Finally, two evaluation criteria including Kappa and area under receiver operating characteristics curve (AUC-ROC) were calculated. According to the findings of this research, MARS had the best performance with AUC-ROC of 84.2%, followed by RF and C5.0 algorithms with AUC-ROC values of 79.7 and 77.3%, respectively. The results indicated that AUC-ROC values for the employed models are more than 70% which shows their acceptable performance. As a conclusion, the produced methodology could be used in other geographical areas. GPMs could be used by water resource managers and related organizations to accelerate and facilitate water resource exploitation.
Jurong Formation underlies part of Southern Johor Bahru which comprises well cemented and consolidated volcanic-sedimentary rocks. The study aims to assess quality and hydrogeochemistry of rock aquifer in Jurong Formation at Southern Johor Bahru which is mainly overlain by rhyolitic tuff. It also evaluates the differences in quality and hydrogeochemistry of rhyolitic tuff aquifer found in source and floodplain zones of South-West Johor Rivers Basin. In this study, a total of nine samples from four wells, namely TW1-TW4, were collected at foothills of Gunung Pulai (TW1) and Iskandar Puteri (TW2-TW4) in Southern Johor Bahru. The samples were examined for physiochemical parameters. The groundwater in the study area is fresh and non-saline with hardness of soft to hard. The pH of groundwater in source zone is significantly higher than in floodplain zone. Meanwhile, the hardness of groundwater in source zone is significantly lower than in other deep wells in floodplain zone as more calcite mineral is present. The concentration of manganese, iron and zinc is lower at source zone than floodplain zone. Three facies of water types were encountered during the study such as CaNaHCO3 in TW2, CaHCO3 in TW1 and TW3 and CaCl2 in TW4. The deep wells in floodplain zone are susceptible to saline intrusion. Finally, the groundwater quality in the study area is found to control by rock weathering especially silicates and carbonates, rainfall and proximity to seawater. This suggests the major control on groundwater chemistry is due to leaching of volcanic rocks and dissolution on calcite infillings. In conclusion, the groundwater is clean and safe in general although pH value is slightly acidic closer to straits and magnesium's presence in higher concentration at TW2.
The research was carried out at 3 study sites with varying groundwater arsenic (As) levels in the Kandal Province of Cambodia. Kampong Kong Commune was chosen as a highly contaminated site (300-500μg/L), Svay Romiet Commune was chosen as a moderately contaminated site (50-300μg/L) and Anlong Romiet Commune was chosen as a control site. Neurobehavioral tests on the 3 exposure groups were conducted using a modified WHO neurobehavioral core test battery. Seven neurobehavioral tests including digit symbol, digit span, Santa Ana manual dexterity, Benton visual retention, pursuit aiming, trail making and simple reaction time were applied. Children's hair samples were also collected to investigate the influence of hair As levels on the neurobehavioral test scores. The results from the inductively coupled plasma-mass spectrometry (ICP-MS) analyses of hair samples showed that hair As levels at the 3 study sites were significantly different (p<0.001), whereby hair samples from the highly contaminated site (n=157) had a median hair As level of 0.93μg/g, while the moderately contaminated site (n=151) had a median hair As level of 0.22μg/g, and the control site (n=214) had a median hair As level of 0.08μg/g. There were significant differences among the 3 study sites for all the neurobehavioral tests scores, except for digit span (backward) test. Multiple linear regression clearly shows a positive significant influence of hair As levels on all the neurobehavioral test scores, except for digit span (backward) test, after controlling for hair lead (Pb), manganese (Mn) and cadmium (Cd). Children with high hair As levels experienced 1.57-4.67 times greater risk of having lower neurobehavioral test scores compared to those with low hair As levels, after adjusting for hair Pb, Mn and Cd levels and BMI status. In conclusion, arsenic-exposed school children from the Kandal Province of Cambodia with a median hair As level of 0.93µg/g among those from the highly contaminated study site, showed clear evidence of neurobehavioral effects.
We investigated relationship of arsenicosis symptoms with total blood arsenic (BAs) and serum albumin (SAlb) of residents in the Mekong River basin of Cambodia. We found that arsenicosis patients had significantly higher BAs and lower SAlb than asymptomatic villagers (Mann-Whitney U test, p<0.01). Arsenicosis symptoms were found to be 76.4% (1.764 times) more likely to develop among individuals having an SAlb≤44.3gL(-1) than among those who had an SAlb>44.3gL(-1) (OR=1.764, 95% CI=0.999-3.114) and 117.6% (2.176 times) as likely to occur among those with BAs>5.73µgL(-1) than for those having BAs≤5.73µgL(-1) (OR=2.176, 95% CI=1.223-3.872). Furthermore, a significant negative correlation was also found between BAs and SAlb (rs (199)=-0.354, p<0.0001). As such, this study suggests that people with low SAlb and/or high BAs are likely to rapidly develop arsenicosis symptoms.
Developing cost-effective technology for treatment of sewage and nitrogen-containing groundwater is one of the crucial challenges of global water industries. Microbial fuel cells (MFCs) oxidize organics from sewage by exoelectrogens on anode to produce electricity while denitrifiers on cathode utilize the generated electricity to reduce nitrogen from contaminated groundwater. As the exoelectrogens are incapable of oxidizing insoluble, polymeric, and complex organics, a novel integration of an anaerobic sequencing batch reactor (ASBR) prior to the MFC simultaneously achieve hydrolytic-acidogenic conversion of complex organics, boost power recovery, and remove Carbon/Nitrogen (C/N) from the sewage and groundwater. The results obtained revealed increases in the fractions of soluble organics and volatile fatty acids in pretreated sewage by 52 ± 19% and 120 ± 40%, respectively. The optimum power and current generation with the pretreated sewage were 7.1 W m-3 and 45.88 A m-3, respectively, corresponding to 8% and 10% improvements compared to untreated sewage. Moreover, the integration of the ASBR with the biocathode MFC led to 217% higher carbon and 136% higher nitrogen removal efficiencies compared to the similar system without ASBR. The outcomes of the present study represent the promising prospects of using ASBR pretreatment and successive utilization of solubilized organics in denitrifying biocathode MFCs for simultaneous energy recovery and C/N removal from both sewage and nitrate nitrogen-contaminated groundwater.
This study was focused on identifying the region suitable for agriculture-based, using new irrigation groundwater quality plot and its spatio-temporal variation with fuzzy logic technique in a geographic information system (GIS) platform. Six hundred and eighty groundwater samples were collected during pre, southwest, northeast, and post monsoon periods. A new ternary plot was also attempted to determine the irrigation suitability of water by considering four essential parameters such as sodium adsorption ratio (SAR), permeability index (PI), Sodium percentage (Na %), and electrical conductivity (EC). The derived ternary plot was the most beneficial over other available plots, as it incorporated four parameters, and it differs from the US Salinity Laboratory (USSL) plot, such that the groundwater with higher EC could also be used for irrigation purposes, depending on the Na%. The ternary plot revealed that the groundwater predominantly manifested good to moderate category during post, northeast, and southwest monsoons. The assessment with the amount of fertilizer used during the study period showed that the NPK fertilizers were effectively used for irrigation during monsoon periods. Spatial maps on EC, Kelly's ratio, Mg hazard, Na%, PI, potential salinity (PS), SAR, residual sodium carbonate (RSC), and soluble sodium percentage (SSP) were prepared for each season using fuzzy membership values, integrated for each season. A final suitability map derived by an overlay of all the seasonal outputs has identified that the groundwater in the western and the eastern part of the study area are suitable for agriculture. The study recommends cultivation of groundwater-dependent short-term crops, along the western and northern regions of the study area during the pre-monsoon season.
Groundwater is a primary natural water source in the absence of surface water bodies. Groundwater in urban environments experiences unprecedented stress from urban growth, population increase, and industrial activities. This study assessed groundwater quality in terms of arsenic and heavy metal contamination in three industrial areas (Shahdara, Jhilmil, and Patparganj), Delhi, India. The water quality was assessed over a 3-year time interval (i.e., 2015 and 2018). The groundwater constituents investigated were As, Fe, Cr, Cd, Ni, Zn, Mn, Cu, and Pb. Metal index and heavy metal pollution indexes were estimated to assess groundwater pollution. The health risk was evaluated in terms of non-carcinogenic and carcinogenic risk assessment. Patparganj industrial area saw increment in concentration for Cu 0.23 mg/L (2015)-0.85 mg/L (2018), Zn 0.51 mg/L (2015)-7.2 mg/L (2018), Fe 0.32 mg/L (2015)-0.9 mg/L (2018), Cr 0.21 mg/L (2015)-0.26 mg/L (2018), Mn 0.14 mg/L (2015)-0.25 mg/L (2018), Ni 0.04 mg/L (2015)-0.34 mg/L (2018), and As 0.01 mg/L (2015)-0.18 mg/L (2018). Cd and Pb concentrations were observed to decrease by 40-90 % and 85-99% for all the three industrial areas. Metal index and heavy metal index values were found to be >1 for all locations. The risk quotient value > 1 was observed for all locations in the year 2015 but was found to increase further to a range of RQ 10-62 in the year 2018, inferring increased non-carcinogenic risk to consumers. The carcinogenic risk was significant with respect to Fe (0.2-0.7), Zn (0.001-0.007), and As (0.002-0.003) for all locations in the year 2015. This study concludes that groundwater in the three industrial areas is highly polluted and is not fit for human consumption. Further studies are required to explore possible control measures and develop methods to mitigate groundwater pollution, sustainable management, and optimized use to conserve it for future generations.
Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes.
In this paper, numerous studies on groundwater in Malaysia were reviewed with the aim of evaluating past trends and the current status for discerning the sustainability of the water resources in the country. It was found that most of the previous groundwater studies (44 %) focused on the islands and mostly concentrated on qualitative assessment with more emphasis being placed on seawater intrusion studies. This was then followed by inland-based studies, with Selangor state leading the studies which reflected the current water challenges facing the state. From a methodological perspective, geophysics, graphical methods, and statistical analysis are the dominant techniques (38, 25, and 25 %) respectively. The geophysical methods especially the 2D resistivity method cut across many subjects such as seawater intrusion studies, quantitative assessment, and hydraulic parameters estimation. The statistical techniques used include multivariate statistical analysis techniques and ANOVA among others, most of which are quality related studies using major ions, in situ parameters, and heavy metals. Conversely, numerical techniques like MODFLOW were somewhat less admired which is likely due to their complexity in nature and high data demand. This work will facilitate researchers in identifying the specific areas which need improvement and focus, while, at the same time, provide policymakers and managers with an executive summary and knowledge of the current situation in groundwater studies and where more work needs to be done for sustainable development.
Hydrogeochemical understanding of groundwater is essential for the effective management of groundwater. This study has been carried out to have concrete data for the seasonal variations in hydrogeochemistry of groundwater in central Tamilnadu forming a complex geological terrain with a varied lithology. A total of 244 groundwater samples were collected during four different seasons, viz, southwest monsoon (SWM), summer (SUM), postmonsoon (POM), and northeast monsoon (NEM) from bore wells. The physical parameters such as pH, temperature, TDS, ORP, humidity, and electrical conductivity (EC) were measured insitu, whereas major ions were analyzed in the lab adopting standard procedures. Overall, higher EC and NO3 values were observed and exceeded the WHO permissible limit irrespective of seasons, except for NO3 in SWM. Na and HCO3 are the dominant cation and anion in the groundwater irrespective of seasons. The highest average values of Na (65.06 mg L-1) and HCO3 (350.75 mg L-1) were noted during SWM. Statistical analysis was carried out to elucidate the hydrogeochemistry of the region. Initially, to understand the ionic relationship, correlation matrix was used followed by factor analysis for determination of major geochemical control and later factor scores were derived to understand the regional representations. An attempt has also been made to identify the samples influenced by multiple geochemical processes and to understand their spatial variation in the study period. Correlation of geochemical parameters reveals a excellent positive correlation between Ca and NO3 in SUM, SWM, and NEM due to the dominant of anthropogenic sources and minor influence of weathering process. Strongly loaded factor scores are found to be mostly in the following order POM > NEM > SWM > SUM. Principal component analysis of different seasons indicates the interplay of natural weathering and anthropogenic factors. Overall, the predominant geochemical processes in this region, irrespective of seasons are weathering and, ion exchange and anthropogenic activities.
In this study, geophysics, geochemistry, and geostatistical techniques were integrated to assess seawater intrusion in Kapas Island due to its geological complexity and multiple contamination sources. Five resistivity profiles were measured using an electric resistivity technique. The results reveal very low resistivity <1 Ωm, suggesting either marine clay deposit or seawater intrusion or both along the majority of the resistivity images. As a result, geochemistry was further employed to verify the resistivity evidence. The Chadha and Stiff diagrams classify the island groundwater into Ca-HCO3, Ca-Na-HCO3, Na-HCO3, and Na-Cl water types, with Ca-HCO3 as the dominant. The Mg(2+)/Mg(2+)+Ca(2+), HCO3 (-)/anion, Cl(-)/HCO3 (-), Na(+)/Cl(-), and SO4 (2-)/Cl(-) ratios show that some sampling sites are affected by seawater intrusion; these sampling sites fall within the same areas that show low-resistivity values. The resulting ratios and resistivity values were then used in the geographical information system (GIS) environment to create the geostatistical map of individual indicators. These maps were then overlaid to create the final map showing seawater-affected areas. The final map successfully delineates the area that is actually undergoing seawater intrusion. The proposed technique is not area specific, and hence, it can work in any place with similar completed characteristics or under the influence of multiple contaminants so as to distinguish the area that is truly affected by any targeted pollutants from the rest. This information would provide managers and policy makers with the knowledge of the current situation and will serve as a guide and standard in water research for sustainable management plan.
Field and laboratory studies were conducted to estimate concentration of potential contaminants from landfill in the underlying groundwater, leachate, and surface water. Samples collected in the vicinity of the landfill were analyzed for physiochemical parameters, organic contaminants, and toxic heavy metals. Water quality results obtained were compared from published data and reports. The results indicate serious groundwater and surface water contamination in and around the waste disposal site. Analysis of the organic samples revealed that the site contains polychlorinated biphenyls and other organo-chlorine chemicals, principally chloro-benzenes. Although the amount of PCB concentration discovered was not extreme, their presence indicates a potentially serious environmental threat. Elevated concentrations of lead, copper, nickel, manganese, cadmium, and cobalt at the downgradient indicate that the contamination plume migrated further from the site, and the distribution of metals and metals containing wastes in the site is nonhomogeneous. These results clearly indicate that materials are poorly contained and are at risk of entering the environment. Therefore, full characterization of the dump contents and the integrity of the site are necessary to evaluate the scope of the problem and to identify suitable remediation options.
In this work, the DRASTIC and GALDIT models were employed to determine the groundwater vulnerability to contamination from anthropogenic activities and seawater intrusion in Kapas Island. In addition, the work also utilized sensitivity analysis to evaluate the influence of each individual parameter used in developing the final models. Based on these effects and variation indices of the said parameters, new effective weights were determined and were used to create modified DRASTIC and GALDIT models. The final DRASTIC model classified the island into five vulnerability classes: no risk (110-140), low (140-160), moderate (160-180), high (180-200), and very high (>200), covering 4, 26, 59, 4, and 7 % of the island, respectively. Likewise, for seawater intrusion, the modified GALDIT model delineates the island into four vulnerability classes: very low (<90), low (90-110), moderate (110-130), and high (>130) covering 39, 33, 18, and 9 % of the island, respectively. Both models show that the areas that are likely to be affected by anthropogenic pollution and seawater intrusion are within the alluvial deposit at the western part of the island. Pearson correlation was used to verify the reliability of the two models in predicting their respective contaminants. The correlation matrix showed a good relationship between DRASTIC model and nitrate (r = 0.58). In a similar development, the correlation also reveals a very strong negative relationship between GALDIT model and seawater contaminant indicator (resistivity Ωm) values (r = -0.86) suggesting that the model predicts more than 86 % of seawater intrusion. In order to facilitate management strategy, suitable areas for artificial recharge were identified through modeling. The result suggested some areas within the alluvial deposit at the western part of the island as suitable for artificial recharge. This work can serve as a guide for a full vulnerability assessment to anthropogenic pollution and seawater intrusion in small islands and will help policy maker and manager with understanding needed to ensure sustainability of the island's aquifer.
This study considered the temporal variations in rainfall and water level patterns as governing factors, which influence the geochemical process of coastal aquifer around Pondicherry, South India. Rainfall and water level data were collected from 2006 to 2016, which showed that the amount of rainfall from 2006 to 2011 was higher than that of 2011 to 2016. To understand the geochemical process governing groundwater, samples were collected during 2006 (n = 54), followed by 2011 (n = 93), and during 2016 (n = 63) as part of continuous observation. The major ions and stable isotopes (δ18O and δD) were analyzed in the samples to determine the geochemical variations. The predominant types were noted as Na-HCO3 and Na-Cl; Ca-HCO3 and Ca-Mg-Cl; and Na-Cl and Ca-Mg-Cl in 2006, 2011, and 2016, respectively. Saturation states of sulfate and carbonate minerals were compared for the study periods and it indicates that the saturation index (SI) values were increased from 2006 to 2011, but decreased from 2011 to 2016. PHREEQC inverse modeling revealed the predominance for the dissolution and leaching of carbonate minerals during increased rainy periods, and the increase of halite saturation during lesser rainfall period. AQUACHEM mixing studies suggested that geochemical signatures of 2006 and 2011 were preserved in samples of 2016 in different proportions. Considering the major factors, the main processes prevailing in the study area were inferred to be dissolution and leaching during 2006~2011 years and seawater intrusion along with ion exchange during 2011~2016 years. In all these periods of study, anthropogenic impact was also identified in the groundwater samples. Hence, this study revealed that the rainfall and water level gave a significant variation in the geochemical process of groundwater in the coastal aquifer system.
Some regions of Argentina are affected by high concentrations of molybdenum, arsenic and vanadium from natural sources in their groundwater. In particular, Mo levels in groundwater from Eduardo Castex (La Pampa, Argentina) typically exceed the guidelines for drinking water formerly established by WHO at 70 μg/L. Therefore, this study investigated the uptake of Mo in plants, using cress (Lepidium sativum L.) as a model using hydroponic experiments with synthetic solutions and groundwater from La Pampa. Cress grown from control experiments (150 μg/L Mo, pH 7) presented an average Mo concentration of 35.2 mg/kg (dry weight, d.w.), higher than the typical total plant range (0.7-2.5 mg/kg d.w.) in the literature. Using pooled groundwater samples (65.0-92.5 μg/L Mo) from wells of La Pampa (Argentina) as growth solutions resulted in significantly lower cress Mo levels (1.89-4.59 mg/kg d.w.) than were obtained for synthetic solutions of equivalent Mo concentration. This may be due to the high levels in these groundwater samples of As, V, Fe and Mn which are known to be associated with volcanic deposits. This research addressed the hitherto scarcity of data about the effect of various physicochemical parameters on the uptake of Mo in plants.