Classified as a small island, Kapas Island experiences major problems especially in supplying freshwater where groundwater abstraction is the only way to meet the demand of drinking water and domestic use. Groundwater samples were collected from seven constructed boreholes to examine the hydrochemistry properties of major ions and in-situ parameters as these could provide a basis for future reference. The chemical composition showed strong and significant correlation for each studied parameter; an indication of the effect of environmental variables to the groundwater composition. The composition changed from Ca-rich to Na-rich are explained mostly by mixing and cation exchange processes. This study provided an input for water management at Kapas Island where groundwater is a crucial resource to maintain the hydrogeological balance of the island.
Groundwater is the main source of water in the Kingdom of Saudi Arabia (KSA). A larger part of groundwater is founded in alluvial (unconfined) aquifers. Prediction of water table elevations in
unconfined aquifers is very useful in water resources planning and management. During the last two
decades, many aquifers in different regions of the KSA experienced significant groundwater decline.
The declines in these aquifers raised concerns over the quantity and quality of groundwater, as well
as concerns over the planning and management policies used in KSA. The main objective of this study was to predict water table fluctuations and to estimate the annual change in water table at an alluvial aquifer at wadi Hada Al Sham near Makkah, KSA. The methodology was achieved using numerical groundwater model (MODFLOW). The model was calibrated and then used to predict water table elevations due to pumping for a period of 5 years. The output of the model was found to be in agreement with the previous records. Moreover, the simulation results also show reasonable declination of water table elevations in the study area during the study period.
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.
Although estimating the uncertainty of models used for modelling nitrate contamination of groundwater is essential in groundwater management, it has been generally ignored. This issue motivates this research to explore the predictive uncertainty of machine-learning (ML) models in this field of study using two different residuals uncertainty methods: quantile regression (QR) and uncertainty estimation based on local errors and clustering (UNEEC). Prediction-interval coverage probability (PICP), the most important of the statistical measures of uncertainty, was used to evaluate uncertainty. Additionally, three state-of-the-art ML models including support vector machine (SVM), random forest (RF), and k-nearest neighbor (kNN) were selected to spatially model groundwater nitrate concentrations. The models were calibrated with nitrate concentrations from 80 wells (70% of the data) and then validated with nitrate concentrations from 34 wells (30% of the data). Both uncertainty and predictive performance criteria should be considered when comparing and selecting the best model. Results highlight that the kNN model is the best model because not only did it have the lowest uncertainty based on the PICP statistic in both the QR (0.94) and the UNEEC (in all clusters, 0.85-0.91) methods, but it also had predictive performance statistics (RMSE = 10.63, R2 = 0.71) that were relatively similar to RF (RMSE = 10.41, R2 = 0.72) and higher than SVM (RMSE = 13.28, R2 = 0.58). Determining the uncertainty of ML models used for spatially modelling groundwater-nitrate pollution enables managers to achieve better risk-based decision making and consequently increases the reliability and credibility of groundwater-nitrate predictions.
Groundwater irrigation is one of the alternative methods to irrigate the paddy crops beside surface water. The use of shallow tube well for paddy irrigation is able to overcome water scarcity especially during dry season and off planting season in Malaysia. The performance of a shallow tube well was evaluated based on well efficiency and pump efficiency. The study was conducted at Seberang Perak Integrated Agricultural Development Area (Seberang Perak IADA). In this study, on-off automatic water controller was installed in the field and connected to the pump system which gave the command to the pump to irrigate the field during pre-saturation and normal growth plantation period. Water level inside the pumping well and cultivation plot was observed and recorded by the water level transducers. The result of the study showed that the pumping well is moderately productive with the well efficiency between 91 and 94%. The submersible pump efficiency was 87.5%. The potential yield of the pumping well was 450 m3day-1 and it was enough and sufficient to irrigate 1 ha of paddy field.
Alluvial aquifers can be found in most of the coastal areas of Peninsular Malaysia. Seven tube wells located in such aquifers in the west coast of Selangor state had their performance evaluated by carryingout step drawdown tests. The performance of these wells was evaluated in terms of aquifer loss, well loss, specific capacity and well efficiency. The aquifer loss coefficient and well loss coefficient were found to be in the range of 0.0198 hrm-2 to 0.4014 hrm-2 and from 0.0001 hr2 m-5 to 0.0410 hr2 m-5, respectively. The drawdown in tube wells TW1 and TW7 is mainly influenced by well loss component as compared to the aquifer loss component, while in tube wells TW2, TW3, TW4, and TW5, the drawdown is mainly influenced by aquifer loss component. The drawdown in tube well TW6 is influenced by aquifer loss component at a low discharge rate, but at high discharge rate, it is influenced by well loss component. The specific capacity and efficiency of the tested tube wells varied from 1.329 m2 hr-1 to 40.166 m2 hr-1, and from 11% to 96%, respectively. Tube wells TW2 and TW4 are categorized as high productive wells, while tube wells TW1, TW3, TW5 and TW7 are categorized as moderate productive wells and tube well TW6 as low productive well.
The contamination of water bodies from heavy metals, either from natural sources or
anthropogenic sources, has become a major concern to the public. Industrial activities with improper
water treatment, and then leach into the water body, have become contaminated and harmful to
consume. Passive remediation is one of the treatments introduced to counter this problem as it is a low
cost but effective technique. After being widely acknowledged and through research conducted, the
most suitable remediation technique found is the permeable reactive barriers (PRBs). PRB is defined
as an in situ permeable treatment zone filled with reactive materials, designed to intercept and
remediate a contaminant plume under natural hydraulic gradients. There have been many findings
made from PRB which can be used to remove contaminants such as heavy metal, chlorinated solvents,
carbonates and aromatic hydrocarbons. The most crucial criteria in making a successful PRB is the
reactive media used to remove contaminants. The current paper presents an overview of the PRB
selective medias that have been used and also the unresolved issue on the long term performance of
PRB. The overall methodology for the application of PRB at a given site is also discussed in this
paper. This inexpensive but effective technique is crucial as a sustainable technology in order to treat
the drainage before it enters water tables to prevent water pollution and can be used as an alternative
raw water source.
The current novel work presents the optimization of factors affecting defluoridation by Al doped ZnO nanoparticles using response surface methodology (RSM). Al doped ZnO nanoparticles were synthesized by the sol-gel method and validated by FTIR, XRD, TEM/EDS, TGA, BET, and particle size analysis. Moreover, a central composite design (CCD) was developed for the experimental study to know the interaction between Al doped ZnO adsorbent dosage, initial concentration of fluoride, and contact time on fluoride removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was achieved to discover the importance of the individual and the effect of variables on the response. The model predicted that the response significantly correlated with the experimental response (R2 = 0.97). Among the factors, the effect of adsorbent dose and contact time was considered to have more influence on the response than the concentration. The optimized process parameters by RSM presented the adsorbent dosage: 0.005 g, initial concentration of fluoride: 1.5 g/L, and contact time: 5 min, respectively. Kinetic, isotherm, and thermodynamic studies were also investigated. The co-existing ions were also studied. These results demonstrated that Al doped ZnO could be a promising adsorbent for effective defluoridation for water.
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.
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.
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.
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.
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.
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.
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.
The current study was conducted to measure the activity concentration of the gross alpha and beta in 87 groundwater samples collected from the productive aquifers that constitute a major source of groundwater to evaluate the annual effective dose and the corresponding health impact on the population and to investigate the quality of groundwater in Jordan. The mean activity concentration of gross alpha and beta in groundwater ranges from 0.26 ± 0.03 to 3.58 ± 0.55 Bq L-1 and from 0.51 ± 0.07 to 3.43 ± 0.46 Bq L-1, respectively. A very strong relationship was found between gross alpha and beta activity concentrations. The annual effective dose for alpha and beta was found in the range of 0.32-2.40 mSv with a mean value of 0.89 mSv, which is nine times higher than the World Health Organization (WHO) recommended limit and one and half times higher than the national regulation limit. The mean lifetime risk was found to be 45.47 × 10-4 higher than the Jordanian estimated upper-bound lifetime risk of 25 × 10-4. The data obtained in the study would be the baseline for further epidemiological studies on health effects related to the exposure to natural radioactivity in Jordan.
Conventional hydrogeologic framework models used to compute ocean island sustainable yields and aquifer storage neglect the complexity of the nearshore and offshore submarine environment. However, the onshore aquifer at the island of Hawai'i exhibits a notable volumetric discrepancy between high-elevation freshwater recharge and coastal discharge. In this study, we present a novel transport mechanism of freshwater moving from onshore to offshore through a multilayer formation of water-saturated layered basalts with interbedded low-permeability layers of ash/soil. Marine electromagnetic imaging reveals ∼35 km of laterally continuous resistive layers that extend to at least 4 km from west of Hawai'i's coastline, containing about 3.5 km3 of freshened water. We propose that this newly found transport mechanism of fresh groundwater may be the governing mechanism in other volcanic islands. In such a scenario, volcanic islands worldwide can use these renewable offshore reservoirs, considered more resilient to climate change-driven droughts, as new water resources.
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.
The dynamics of the coastal aquifers are well-expressed by geochemical and isotopic signatures. Coastal regions often exhibit complex groundwater recharge pattern due to the influence of depression in the Bay of Bengal, tidal variations on surface waters, saline water intrusion and agricultural return flows. In this research, groundwater recharge processes occurring in coastal Tamil Nadu, South India were evaluated using major ion chemistry and environmental isotopes. A total of 170 groundwater samples were collected from shallow and deep aquifers during both post-monsoon (POM) and pre-monsoon (PRM) seasons. The isotopic results showed a wide variation in the shallow groundwater, suggesting contribution from multiple recharge sources. But, the deeper groundwater recharge is mainly from precipitation. The northern part of the study area showed more depleted isotopic values, which rapidly changed towards south from -6.8 to -4.4‰. Alternatively, central and southern parts exhibited relatively enriched isotopic content with variation from -0.58 to -2.7‰. Groundwater was discerned to be brackish to saline with chloride content, 600-2060 mgL-1 and δ18O ranging from -5.8 to -4.5‰, suggesting influence of the saline water sources. A minor influence of anthropogenic activities was also observed in the deeper groundwater during PRM, which was confirmed by tritium and Cl- trends. The old groundwater with depleted isotopic content infer recharged by distant sources while modern groundwater with enriched isotopes points to the influence of evaporated recharge.
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.