Hydrogeochemical investigations had been carried out at the Amol-Babol Plain in the north of Iran. Geochemical processes and factors controlling the groundwater chemistry are identified based on the combination of classic geochemical methods with geographic information system (GIS) and geostatistical techniques. The results of the ionic ratios and Gibbs plots show that water rock interaction mechanisms, followed by cation exchange, and dissolution of carbonate and silicate minerals have influenced the groundwater chemistry in the study area. The hydrogeochemical characteristics of groundwater show a shift from low mineralized Ca-HCO3, Ca-Na-HCO3, and Ca-Cl water types to high mineralized Na-Cl water type. Three classes, namely, C1, C2, and C3, have been classified using cluster analysis. The spatial distribution maps of Na(+)/Cl(-), Mg(2+)/Ca(2+), and Cl(-)/HCO3 (-) ratios and electrical conductivity values indicate that the carbonate and weathering of silicate minerals played a significant role in the groundwater chemistry on the southern and western sides of the plain. However, salinization process had increased due to the influence of the evaporation-precipitation process towards the north-eastern side of the study area.
Uranium is a radioactive element normally present in hexavalent form as U(VI) in solution and elevated levels in drinking water cause health hazards. Representative groundwater samples were collected from different litho-units in this region and were analyzed for total U and major and minor ions. Results indicate that the highest U concentration (113 µg l(-1)) was found in granitic terrains of this region and about 10 % of the samples exceed the permissible limit for drinking water. Among different species of U in aqueous media, carbonate complexes [UO2(CO3)(2)(2-)] are found to be dominant. Groundwater with higher U has higher pCO2 values, indicating weathering by bicarbonate ions resulting in preferential mobilization of U in groundwater. The major minerals uraninite and coffinite were found to be supersaturated and are likely to control the distribution of U in the study area. Nature of U in groundwater, the effects of lithology on hydrochemistry and factors controlling its distribution in hard rock aquifers of Madurai district are highlighted in this paper.
In recent years, groundwater quality has become a global concern due to its effect on human life and natural ecosystems. To assess the groundwater quality in the Amol-Babol Plain, a total of 308 water samples were collected during wet and dry seasons in 2009. The samples were analysed for their physico-chemical and biological constituents. Multivariate statistical analysis and geostatistical techniques were applied to assess the spatial and temporal variabilities of groundwater quality and to identify the main factors and sources of contamination. Principal component analysis (PCA) revealed that seven factors explained around 75% of the total variance, which highlighted salinity, hardness and biological pollution as the dominant factors affecting the groundwater quality in the Plain. Two-way analysis of variance (ANOVA) was conducted on the dataset to evaluate the spatio-temporal variation. The results showed that there were no significant temporal variations between the two seasons, which explained the similarity between six component factors in dry and wet seasons based on the PCA results. There are also significant spatial differences (p > 0.05) of the parameters under study, including salinity, potassium, sulphate and dissolved oxygen in the plain. The least significant difference (LSD) test revealed that groundwater salinity in the eastern region is significantly different to the central and western side of the study area. Finally, multivariate analysis and geostatistical techniques were combined as an effective method for demonstrating the spatial structure of multivariate spatial data. It was concluded that multiple natural processes and anthropogenic activities were the main sources of groundwater salinization, hardness and microbiological contamination of the study area.
The presence of radioactive elements in groundwater results in high health risks on surrounding populations. Hence, a study was conducted in central Tamil Nadu, South India, to measure the radon levels in groundwater and determine the associated health risk. The study was conducted along the lithological contact of hard rock and sedimentary formation. The concentrations of uranium (U) varied from 0.28 to 84.65 µg/L, and the radioactivity of radon (Rn) varied from 258 to 7072 Bq/m3 in the collected groundwater samples. The spatial distribution of Rn in the study area showed that higher values were identified along the central and northern regions of the study area. The data also indicate that granitic and gneissic rocks are the major contributors to Rn in groundwater through U-enriched lithological zones. The radon levels in all samples were below the maximum concentration level, prescribed by Environmental Protection Agency. The effective dose levels for ingestion and inhalation were calculated according to parameters introduced by UNSCEAR and were found to be lesser (0.235-6.453 μSvy-1) than the recommended limit. Hence, the regional groundwater in the study area does not pose any health risks to consumers. The spatial distribution of Rn's effective dose level indicates the higher values were mainly in the central and northern portion of the study area consist of gneissic, quarzitic, and granitic rocks. The present study showed that Rn concentrations in groundwater depend on the lithology, structural attributes, the existence of uranium minerals in rocks, and the redox conditions. The results of this study provide information on the spatial distribution of Rn in the groundwater and its potential health risk in central Tamil Nadu, India. It is anticipated that these data will help policymakers to develop plans for management of drinking water resources in the region.
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.
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.
Nitrate concentration in groundwater is influenced by complex and interrelated variables, leading to great difficulty during the modeling process. The objectives of this study are (1) to evaluate the performance of two artificial intelligence (AI) techniques, namely artificial neural networks and support vector machine, in modeling groundwater nitrate concentration using scant input data, as well as (2) to assess the effect of data clustering as a pre-modeling technique on the developed models' performance. The AI models were developed using data from 22 municipal wells of the Gaza coastal aquifer in Palestine from 2000 to 2010. Results indicated high simulation performance, with the correlation coefficient and the mean average percentage error of the best model reaching 0.996 and 7 %, respectively. The variables that strongly influenced groundwater nitrate concentration were previous nitrate concentration, groundwater recharge, and on-ground nitrogen load of each land use land cover category in the well's vicinity. The results also demonstrated the merit of performing clustering of input data prior to the application of AI models. With their high performance and simplicity, the developed AI models can be effectively utilized to assess the effects of future management scenarios on groundwater nitrate concentration, leading to more reasonable groundwater resources management and decision-making.
Groundwater chemistry of small tropical islands is influenced by many factors, such as recharge, weathering and seawater intrusion, among others, which interact with each other in a very complex way. In this work, multivariate statistical analysis was used to evaluate the factors controlling the groundwater chemistry of Kapas Island (Malaysia). Principal component analysis (PCA) was applied to 17 hydrochemical parameters from 108 groundwater samples obtained from 18 sampling sites. PCA extracted four PCs, namely seawater intrusion, redox reaction, anthropogenic pollution and weather factors, which collectively were responsible for more than 87% of the total variance of the island's hydrochemistry. The cluster analysis indicated that three factors (weather, redox reaction and seawater intrusion) controlled the hydrochemistry of the area, and the variables were allocated to three groups based on similarity. A Piper diagram classified the island's water types into Ca-HCO3 water type, Na-HCO3 water type, Na-SO4-Cl water type and Na-Cl water type, indicating recharge, mixed, weathering and leached from sewage and seawater intrusion, respectively. This work will provide policy makers and land managers with knowledge of the precise water quality problems affecting the island and can also serve as a guide for hydrochemistry assessments of other islands that share similar characteristics with the island in question.
Natural, inorganic arsenic contamination of groundwater threatens the health of more than 100 million people worldwide, including residents of the densely populated river deltas of South and Southeast Asia. Contaminated groundwater from tube wells in Cambodia was discovered in 2001 leading to the detection of the first cases of arsenicosis in 2006. The most affected area was the Kandal Province. The main objective of this study was to determine the prevalence of arsenicosis in Cambodia based on acceptable criteria, and to investigate the use of hair arsenic as a biomarker not only for arsenicosis-related signs but also for associated symptoms. A cross-sectional epidemiological study of 616 respondents from 3 purposely selected provinces within the Mekong River basin of Cambodia was conducted. The Kandal Province was chosen as a high arsenic-contaminated area, while the Kratie Province and Kampong Cham Province were chosen as moderate and low arsenic-contaminated areas, respectively. The most prevalent sign of arsenicosis was hypomelanosis with a prevalence of 14.5% among all respondents and 32.4% among respondents with a hair arsenic level of ≥1 μg/g. This was followed by hyperkeratosis, hyperpigmentation and mee's lines. Results also suggest a 1.0 μg/g hair arsenic level to be a practical cut off point for an indication of an arsenic contaminated individual. This hair arsenic level, together with the presence of one or more of the classical signs of arsenicosis, seems to be a practical criteria for a confirmed diagnosis. Based on these criteria, the overall prevalence of arsenicosis for all provinces was found to be 16.1%, with Kandal Province recording the highest prevalence of 35.5%. This prevalence is comparatively high when compared to that of other affected countries. The association between arsenicosis and the use of Chinese traditional medicine also needs further investigation.
To evaluate the current status of arsenic exposure in the Mekong River basin of Cambodia, field interview along with urine sample collection was conducted in the arsenic-affected area of Kandal Province, Cambodia. Urine samples were analyzed for total arsenic concentrations by inductively coupled plasma mass spectrometry. As a result, arsenicosis patients (n = 127) had As in urine (UAs) ranging from 3.76 to 373 µg L(-1) (mean = 78.7 ± 69.8 µg L(-1); median = 60.2 µg L(-1)). Asymptomatic villagers (n = 108) had UAs ranging from 5.93 to 312 µg L(-1) (mean = 73.0 ± 52.2 µg L(-1); median = 60.5 µg L(-1)). About 24.7 % of all participants had UAs greater than 100 µg L(-1) which indicated a recent arsenic exposure. A survey found that females and adults were more likely to be diagnosed with skin sign of arsenicosis than males and children, respectively. Education level, age, gender, groundwater drinking period, residence time in the village and amount of water drunk per day may influence the incidence of skin signs of arsenicosis. This study suggests that residents in Kandal study area are currently at risk of arsenic although some mitigation has been implemented. More commitment should be made to address this public health concern in rural Cambodia.
Analytical study of the influence of both the pumping well discharge rate and pumping time on contaminant transport and attenuation is significant for hydrological and environmental science applications. This article provides an analytical solution for investigating the influence of both pumping time and travelling time together for one-dimensional contaminant transport in riverbank filtration systems by using the Green's function approach. The basic aim of the model is to understand how the pumping time and pumping rate, which control the travelling time, can affect the contaminant concentration in riverbank filtration systems. Results of analytical solutions are compared with the results obtained using a MODFLOW numerical model. Graphically, it is found that both analytical and numerical solutions have almost the same behaviour. Additionally, the graphs indicate that any increase in the pumping rate or simulation pumping time should increase the contamination in groundwater. The results from the proposed analytical model are well matched with the data collected from a riverbank filtration site in France. After this validation, the model is then applied to the first pilot project of a riverbank filtration system conducted in Malaysia. Sensitivity analysis results highlight the importance of degradation rates of contaminants on groundwater quality, for which higher utilization rates lead to the faster consumption of pollutants.
Malaysia has abundant sources of drinking water from river and groundwater. However, rapid developments have deteriorated quality of drinking water sources in Malaysia. Heavy metal studies in terms of drinking water, applications of health risk assessment and bio-monitoring in Malaysia were reviewed from 2003 to 2013. Studies on heavy metal in drinking water showed the levels are under the permissible limits as suggested by World Health Organization and Malaysian Ministry of Health. Future studies on the applications of health risk assessment are crucial in order to understand the risk of heavy metal exposure through drinking water to Malaysian population. Among the biomarkers that have been reviewed, toenail is the most useful tool to evaluate body burden of heavy metal. Toenails are easy to collect, store, transport and analysed. This review will give a clear guidance for future studies of Malaysian drinking water. In this way, it will help risk managers to minimize the exposure at optimum level as well as the government to formulate policies in safe guarding the population.
Generally, non-nutritive artificial sweeteners are widely utilized as sugar substitute in various applications. With various applications, non-nutritive artificial sweeteners are now being recognized as emerging contaminants with high water persistence and are chemically stable in environment. Although non-nutritive artificial sweeteners were documented on their occurrence in environment, yet their potential impacts to environment and human health remain ambiguous. Therefore, this review was prepared to provide a more comprehensive insight of non-nutritive artificial sweeteners in environment matrixes by highlighting special concerns on human health and environmental risks. Precisely, this review monitors the exploration of non-nutritive artificial sweeteners occurrences as an emerging contaminants in environment worldwide and their associated risks to human as well as environment. At present, there are a total of 24 non-nutritive artificial sweeteners' studies with regards to their occurrence in the environment from 38 locations globally, spanning across Europe including United Kingdoms, Canada, United States and Asia. Overall, the quantitative findings suggested that the occurrence of non-nutritive artificial sweeteners is present in surface water, tap water, groundwater, seawater, lakes and atmosphere. Among these environmental matrixes, surface water was found as the most studied matrix involving non-nutritive artificial sweeteners. However, findings on non-nutritive artificial sweeteners impacts on human health and environment are limited to understanding its overall potential impacts and risks. Additionally, this review also serves as a framework for future monitoring plans and environmental legislative to better control these emerging contaminants in environment.
Microbes in groundwater play a key role in determining the drinking water quality of the water. The study aims to interpret the sources of microbes in groundwater and its relationship to geochemistry. The study was carried out by collecting groundwater samples and analyzed to obtain various cations and anions, where HCO3-, Cl- and NO3- found to be higher than permissible limits in few samples. Microbial analysis, like total coliform (TC), total viable counts (TVC), fecal coliforms (FC), Vibrio cholera (V. cholerae) and total Streptococci (T. streptococci) were analyzed, and the observations reveal that most of the samples were found to be above the permissible limits adopted by EU, BIS, WHO and USEPA standards. Correlation analysis shows good correlation between Mg2+-HCO3-, K+-NO3-, TVC- V. cholerae and T. streptococci-FC. Major ions like Mg+, K+, NO3, Ca2+ and PO4 along with TS and FC were identified to control the geochemical and microbial activities in the region. The magnesium hardness in the groundwater is inferred to influence the TVC and V. cholerae. The mixing of effluents from different sources reflected the association of Cl with TC. Population of microbes T. streptococci and FC was mainly associated with Ca and Cl content in groundwater, depicting the role of electron acceptors and donors. The sources of the microbial population were observed with respect to the land use pattern and the spatial distribution of hydrogeochemical factors in the region. The study inferred that highest microbial activity in the observed in the residential areas, cultivated regions and around the landfill sites due to the leaching of sewage water and fertilizers runoff into groundwater. The concentrations of ions and microbes were found to be above the permissible limits of drinking water quality standards. This may lead to the deterioration in the health of particular coastal region.
Evaluation of the hydrogeochemical processes governing the heavy metal distribution and the associated health risk is important in managing and protecting the health of freshwater resources. This study mainly focused on the health impacts due to the heavy metals pollution in a known Cretaceous-Tertiary (K/T) contact region (Tiruchinopoly, Tamilnadu) of peninsular India, using various pollution indices, statistical, and geochemical analyses. A total of 63 samples were collected from the hard rock aquifers and sedimentary formations during southwest monsoon and analysed for heavy metals, such as Li, Be, Al, Rb, Sr, Cs, Ba, pb, Mn, Fe, Cr, Zn, Ga, Cu, As, Ni, and Co. Ba was the dominant element that ranged from 441 to 42,638 μg/l in hard rock aquifers, whereas Zn was the major element in sedimentary formations, with concentrations that ranged from 44 to 118,281 μg/l. The concentrations of Fe, Ni, Cr, Al, Cr, and Ni fell above the permissible limit in both of the formations. However, the calculated heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and the degree of contamination (Cd) parameters were higher in the sedimentary formation along the contact zone of the K/T boundary. Excessive health risks from consumption of contaminated groundwater were mostly confined to populations in the northern and southwestern regions of the study area. Carcinogenic risk assessment suggests that there are elevated risks of cancer due to prolonged consumption of untreated groundwater. Ba, Sr, and Zn were found to be geochemically highly mobile due to the partitioning between the rock matrix and groundwater, aided by the formation of soluble carbonato-complexes. Factor analysis indicates that the metals are mainly derived from the host rocks and anthropogenic inputs are relatively insignificant. Overall, this study indicated that groundwater in K/T contact zones is vulnerable to contamination because of the favorable geochemical factors. Long-term monitoring of such contact zones is required to avert the potential health hazards associated with consumption of the contaminated groundwater.
A comprehensive study was conducted to identify the salinization origins and the major hydrogeochemical processes controlling the salinization and deterioration of the Gaza coastal aquifer system through a combination approaches of statistical and geostatistical techniques, and detailed hydrogeochemical assessments. These analyses were applied on ten physicochemical variables for 219 wells using STATA/SE12 and Surfer softwares. Geostatistical analysis of the groundwater salinity showed that seawater intrusion along the coastline, and saltwater up-coning inland highly influenced the groundwater salinity of the study area. The hierarchical cluster analysis (HCA) technique yielded seven distinct hydrogeochemical signature clusters; (C1&C2: Eocene brackish water invasion, C3 saltwater up-coning, C4 human inputs, C5 seawater intrusion, C6 & C7 rainfall and mixing inputs). Box plot shows a wide variation of most of the ions while Chadha's plot elucidates the predominance of Na-Cl (71.6%) and Ca/Mg-Cl (25%) water types. It is found that, the highest and the lowest levels of salinization and the highest level of nitrate pollution were recorded in the northern area. This result reflects the sensitivity of this area to the human activities and/or natural actions. Around 90.4% of the wells are nitrate polluted. The main source of nitrate pollution is the sewage inputs while the farming inputs are very limited and restricted mostly in the sensitive northern area. Among the hydrogeochemical processes, ion exchange process was the most effective process all over the study area. Carbonate dissolution was common in the study area with the highest level in clusters 6, 7, 4 and 2 in the north while Gypsum dissolution was significant only in cluster 1 in the south and limited in the other clusters. This integrated multi-techniques research should be of benefit for effective utilization and management of the Gaza coastal aquifer system as well as for future work in other similar aquifers systems.
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 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.
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.
The aim of the present study was to assess the drinking water quality in the selected urban areas of Lahore and to comprehend the public health status by addressing the basic drinking water quality parameters. Total 50 tap water samples were collected from groundwater in the two selected areas of district Lahore i.e., Gulshan-e-Ravi (site 1) and Samanabad (site 2). Water samples were analyzed in the laboratory to elucidate physico-chemical parameters including pH, turbidity, temperature, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), total hardness, magnesium hardness, and calcium hardness. These physico-chemical parameters were used to examine the Water Quality Index (WQI) and Synthetic Pollution Index (SPI) in order to characterize the water quality. Results of th selected physico-chemical parameters were compared with World Health Organization (WHO) guidelines to determine the quality of drinking water. A GIS-based approach was used for mapping water quality, WQI, and SPI. Results of the present study revealed that the average value of temperature, pH, and DO of both study sites were within the WHO guidelines of 23.5 °C, 7.7, and 6.9 mg/L, respectively. The TDS level of site 1 was 192.56 mg/L (within WHO guidelines) and whereas, in site 2 it was found 612.84 mg/L (higher than WHO guidelines), respectively. Calcium hardness of site 1 and site 2 was observed within the range from 25.04 to 65.732 mg/L but, magnesium hardness values were higher than WHO guidelines. The major reason for poor water quality is old, worn-out water supply pipelines and improper waste disposal in the selected areas. The average WQI was found as 59.66 for site 1 and 77.30 for site 2. Results showed that the quality of the water was classified as "poor" for site 1 and "very poor " for site 2. There is a need to address the problem of poor water quality and also raise the public awareness about the quality of drinking water and its associated health impacts.