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.
Contamination of groundwater by harmful substances poses significant risks to both drinking water sources and aquatic ecosystems, making it a critical environmental concern. Most on-land spill events release organic molecules known as light non-aqueous phase liquids (LNAPLs), which then seep into the ground. Due to their low density and organic composition, they tend to float as they reach the water table. LNAPLs encompass a wide range of non-aqueous phase liquids, including various petroleum products, and can, over time, develop carcinogenic chemicals in water. However, due to frequent changes in hydraulic head, the confinement may fail to contain them, causing them to extend outward. When it contaminates water wells, people cannot reliably consume the water. The removal of dangerous contaminants from groundwater aquifers is made more challenging by LNAPLs. It is imperative to analyze the mechanisms governing LNAPL migration. As a response to this need and the associated dispersion of contaminants into adjacent aquifers, we have conducted a comprehensive qualitative literature review encompassing the years 2000-2022. Groundwater variability, soil structure, and precipitation have been identified as the three primary influential factors, ranked in the following order of significance. The rate of migration is shown to rise dramatically in response to changes in groundwater levels. Different saturation zones and confinement have a major effect on the lateral migration velocity. When the various saturation zones reach a balance, LNAPLs will stop moving. Although higher confinement slows the rate of lateral migration, it speeds up vertical migration. Beyond this, the lateral or vertical movement is also influenced by differences in the permeability of soil strata. Reduced mobility and tighter containment are the outcomes of migrating through fine-grained, low-porosity sand. The gaseous and liquid phases of LNAPLs move more quickly through coarse-grained soils. Due to the complexities and uncertainties associated with LNAPL behavior, accurately foreseeing the future spread of LNAPLs can be challenging. Although studies have utilized modeling techniques to simulate and predict LNAPL migration, the inherent complexities and uncertainties in the subsurface environment make it difficult to precisely predict the extent of LNAPL spread in the future. The granular soil structure considerably affects the porosity and pore pressure.
This paper reviewed the impacts of climate change on the management of the water sector in Malaysia discussing the current status of water resources, water service, and water-related disasters. The implementation of engineering practices was discussed to provide the detailed assessment of climate change impacts, risks, and adaptation for sustainable development. The narrative methods of reviewing the literatures were used to get an understanding on the engineering practices of water infrastructures, implication of the government policies, and several models as the main motivation behind the concept of integrated water resource management to contribute as part of the sustainable development goals to achieve a better and more sustainable future for all. The findings of this review highlighted the impacts of climate change on the rivers, sea, lakes, dams, and groundwater affecting the availability of water for domestic and industrial water supplies, irrigation, hydropower, and fisheries. The impacts of climate change on the water-related disasters have been indicated affecting drought-flood abrupt alternation and water pollution. Challenges of water management practices facing climate change should be aware of the updated intensity-duration-frequency curves, alternative sources of water, effective water demand management, efficiency of irrigation water, inter-basin water transfer, and nonrevenue water. The transferability of this review findings contribute to an engagement with the society and policy makers to mobilize for climate change adaptation in the water sector.
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.
In recent times, surface water resource in the Western Region of Ghana has been found to be inadequate in supply and polluted by various anthropogenic activities. As a result of these problems, the demand for groundwater by the human populations in the peri-urban communities for domestic, municipal and irrigation purposes has increased without prior knowledge of its water quality. Water samples were collected from 14 public hand-dug wells during the rainy season in 2013 and investigated for total coliforms, Escherichia coli, mercury (Hg), arsenic (As), cadmium (Cd) and physicochemical parameters. Multivariate statistical analysis of the dataset and a linear stoichiometric plot of major ions were applied to group the water samples and to identify the main factors and sources of contamination. Hierarchal cluster analysis revealed four clusters from the hydrochemical variables (R-mode) and three clusters in the case of water samples (Q-mode) after z score standardization. Principal component analysis after a varimax rotation of the dataset indicated that the four factors extracted explained 93.3 % of the total variance, which highlighted salinity, toxic elements and hardness pollution as the dominant factors affecting groundwater quality. Cation exchange, mineral dissolution and silicate weathering influenced groundwater quality. The ranking order of major ions was Na(+) > Ca(2+) > K(+) > Mg(2+) and Cl(-) > SO4 (2-) > HCO3 (-). Based on piper plot and the hydrogeology of the study area, sodium chloride (86 %), sodium hydrogen carbonate and sodium carbonate (14 %) water types were identified. Although E. coli were absent in the water samples, 36 % of the wells contained total coliforms (Enterobacter species) which exceeded the WHO guidelines limit of zero colony-forming unit (CFU)/100 mL of drinking water. With the exception of Hg, the concentration of As and Cd in 79 and 43 % of the water samples exceeded the WHO guideline limits of 10 and 3 μg/L for drinking water, respectively. Reported values in some areas in Nigeria, Malaysia and USA indicated that the maximum concentration of Cd was low and As was high in this study. Health risk assessment of Cd, As and Hg based on average daily dose, hazard quotient and cancer risk was determined. In conclusion, multiple natural processes and anthropogenic activities from non-point sources contributed significantly to groundwater salinization, hardness, toxic element and microbiological contamination of the study area. The outcome of this study can be used as a baseline data to prioritize areas for future sustainable development of public wells.
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.
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.
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.
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.
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.
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.