Groundwater Quality Parameters Research Articles

An index based quality evaluation of groundwater—a case study of Whitefield area in Bangalore, India

ABSTRACT Conventional indices to describe the quality of water have been found to have several drawbacks. Hence, an attempt has been made to overcome these deficiencies by developing an improved system by incorporating a few modifications in the drinking water quality indices developed hitherto. Fifteen groundwater quality parameters were chosen for the study and categorised into four groups based on potability and hazard factor. These parameters were analysed for water samples drawn from 30 groundwater sources in the study area. A proposed drinking water quality index (PDWQI) was arrived at, and this was compared with the arithmetic and geometric indices as evaluated in this study, to depict its utility and adaptability. The results revealed that the geometric DWQI was higher than the arithmetic as well as proposed DWQI, while the geometric DWQI was lower than the proposed DWQI. All the indices had a high positive correlation (r = +0.99). The PDWQI clearly illustrated the degree of potability of groundwater for drinking purposes in regard of health threats, by indicating the degree of pollution caused by the various quality parameters. The comparison between the three indices clearly depicted that the PDWQI was the most reliable water quality indexing system, which enabled the reduction of issues of eclipsing as well as sensitivity, that is found to exist in conventional indexing systems.

Groundwater Quality Evaluation for Potable Use and Associated Human Health Risk in Gaobeidian City, North China Plain

The groundwater in Gaobeidian city is used for drinking, irrigation, industrial production, and other purposes. With the rapid development of the economy and urbanization, groundwater quality has been seriously affected. The main purposes of this paper are to evaluate the groundwater quality in the study area on the basis of understanding the hydrochemical characteristics of the study area and assess the possible health risks of groundwater to children and adults. In this paper, the entropy weight method was used to determine the weight of each evaluation parameter, and on this basis, groundwater quality evaluation was carried out, and the spatial distribution map of groundwater quality was drawn according to the evaluation results. The results show that the weight values of the five parameters of NO2–, Fe, As, Cr6+, and NO2–N are more than 0.1 among the total of fifteen parameters, and the concentration of these five parameters can be considered as the main influencing parameters of groundwater quality. The calculation results of the entropy weighted water quality index (EWQI) show that all the groundwater quality in the study area is class 1 water, which is Excellent Water. However, the EWQI value is the highest in the southwest of the study area, showing a trend of deterioration of groundwater water quality. Since all groundwater samples were evaluated as “excellent water,” it was speculated that the natural environment had more influence on groundwater chemical characteristics than human factors. The study found that 7.407% and 55.556% of the water samples posed a noncarcinogenic health risk to adults and children, respectively. The main responsible parameters for noncarcinogenic risk are F−, NO2−, NO3−, and Cr6+. The carcinogenic risk for adults ranged from 0 to 6.91E-04, with a mean of 1.00E-04. The carcinogenic risk for children ranged from 0 to 1.03E-03, with a mean of 1.55E-04. These toxic elements are mainly from industries. Therefore, the deterioration of groundwater quality can be prevented by strengthening the sewage management of various industries.

Groundwater quality assessment using principal component analysis and hierarchical cluster analysis in Alaçam, Turkey

Abstract This study assessed groundwater quality in Alaçam, where irrigations are performed solely with groundwaters and samples were taken from 35 groundwater wells at pre and post irrigation seasons in 2014. Samples were analyzed for 18 water quality parameters. SAR, RSC and %Na values were calculated to examine the suitability of groundwater for irrigation. Hierarchical cluster analysis and principal component analysis were used to assess the groundwater quality parameters. The average EC value of groundwater in the pre-irrigation period was 1.21 dS/m and 1.30 dS/m after irrigation in the study area. It was determined that there were problems in two wells pre-irrigation and one well post-irrigation in terms of RSC, while there was no problem in the wells in terms of SAR. Piper diagram and cluster analysis showed that most groundwaters had CaHCO3 type water characteristics and only 3% had NaCl- as the predominant type. Seawater intrusion was identified as the primary factor influencing groundwater quality. Multivariate statistical analyses to evaluate polluting sources revealed that groundwater quality is affected by seawater intrusion, ion exchange, mineral dissolution and anthropogenic factors. The use of multivariate statistical methods and geographic information systems to manage water resources will be beneficial for both planners and decision-makers.

Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models.

Forecasting the irrigation groundwater parameters helps plan irrigation water and crop, and it is commonly expensive because it needs various parameters, mainly in developing nations. Therefore, the present research's core objective is to create accurate and reliable machine learning models for irrigation parameters. To accomplish this determination, three machine learning (ML) models, viz. long short-term memory (LSTM), multi-linear regression (MLR), and artificial neural network (ANN), have been trained. It is validated with mean squared error (MSE) and correlation coefficients (r), root mean square error (RMSE), and mean absolute error (MAE). These machine learning models have been used and applied for predicating the six irrigation water quality parameters such as sodium absorption ratio (SAR), percentage of sodium (%Na), residual sodium carbonate (RSC), magnesium hazard (MH), Permeability Index (PI), and Kelly ratio (KR). Therefore, the two scenario performances of ANN, LSTM, and MLR have been developed for each model to predict irrigation water quality parameters. The first and second scenario performance was created based on all and second reduction input variables. The ANN, LSTM, and MLR models have discovered that excluding for ANN and MLR models shows high accuracy in first and second scenario models, respectively. These model's accuracy was checked based on the mean squared error (MSE), correlation coefficients (r), and root mean square error (RMSE) for training and testing processes serially. The RSC values are highly accurate predicated values using ANN and MLR models. As a result, machine learning models may improve irrigation water quality parameters, and such types of results are essential to farmers and crop planning in various irrigation processes.

Spatial distribution change of groundwater quality in deep aquifer of Semarang alluvial plains area in past five years

Over time, excessive groundwater usage in urban areas can affect groundwater conditions both in quantity & quality. In some regions, groundwater in the unconfined aquifer has been heavily involved, but for confined aquifers that are deep & tend to be protected, they are not involved too much. The extensive effect, especially groundwater quality, is very significant, especially in coastal areas where seawater intrusion is common & changes in water salinity occur within a specific time range. Regarding these conditions, research was carried out related to changes in spatial & temporal distribution patterns of groundwater quality, exceedingly physical & chemical parameters related to salinity in confined aquifer conditions in coastal areas. By taking a case study in the alluvial plains of Semarang City, this study aims to determine whether there are significant changes in the five years, starting from 2016 to 2020. By using data sourced from groundwater quality tests taken in the reference year, the results gained from the data processing explained that the groundwater quality parameters such as electrical conductivity, total dissolved solids (TDS), acidity (pH), & chloride ions (Cl-) are changing respectively, both spatially & temporally.

Assessment of physicochemical characteristics in groundwater quality parameters

The assessment of groundwater quality was carried out by fetching the groundwater samples from different locations of Tandojam. The physicochemical parameters of groundwater samples were assessed to determine their quality and suitability for usage. The findings of the study have comprehensively demonstrated the presence of high quantity physicochemical parameters in most of the areas in contrast to guidelines values by the World Health Organization (WHO) and National Environmental Quality Standards (NEQS) for drinking water. Only Boron from all locations was best suitable within the limits of the guidelines. However, TDS, pH, EC, TH, turbidity, Cl ion, Al, SO42−, and NO3− were exceeding the WHO guidelines in most of the locations, and the quantified values were noticed within the limits only in few locations. Moreover, the TDS concentration of the Sindh Agriculture University colony was within the limits. In the Garibabad colony, Shahi Bazar, and Pakistani Chowk, the condition of the water is very displeasing because samples from these areas contained salty taste as well as high hardness. The correlation analysis among different parameters showed that as the correlations between parameters became weaker, the observed values became insignificant. The linear regression analysis was done as well as models were developed for predicting the concentration of groundwater quality parameters. A significantly positive correlation at 1% and 5% was found between many parameters. The regression model of turbidity presented a maximum value of 0.948% of the observed variability.

An Enhanced Weight Update Method for Simplified ARTMAP to Classify Groundwater Data

The groundwater for aquatic purposes must be assessed prior to its consumption. Huge number of conventional methods are existing for assessing the quality of groundwater. The water quality index is one of the important conventional methods to assess the groundwater quality. But the conventional methods alone are not enough to assess groundwater quality as well as classify based on its purity. In this paper, we propose an enhanced weight update method for Simplified Fuzzy Adaptive Resonance Theory model to classify the groundwater quality depending on the relative weights of the groundwater quality parameters. Finding the optimal weights is the key to achieve better accuracy of the model, most of the nonlinear models fails to exhibit good accuracy if they fail to learn the optimal weights in the learning process. The aim of the work is to find the good fit between the predicted and the actual groundwater quality grades by identifying the optimal weights of the network by the enhanced weight update method. The Simplified Fuzzy Adaptive Resonance Theory map with the enhanced weight update method performance is justified by comparing it with the Simplified Fuzzy Adaptive Resonance Theory Map. The enhanced weight update method improves the accuracy of the Simplified Fuzzy Adaptive Resonance Theory Map in classifying and predicting the groundwater quality.

Trace elements in groundwater near an abandoned mine tailings dam and health risk assessment (NE Zimbabwe)

Groundwater from shallow hand-dug wells at an abandoned gold mine tailings dam was characterised for selected physicochemical parameters during dry and wet seasons of 2018 and 2019. Health risk exposure of the local population (adults and children) through ingestion and dermal exposure was assessed. Groundwater quality parameters were lower than international drinking water quality guidelines (p < 0.05). The parameters were significantly influenced by season of the year (As, Cl−, SO42−), nature (As, Cd, Cl−, Fe, NO3−, SO42−), depth (Cd, Cl−, Fe, Ni, SO42−) and direction of the well (Cu, Cl−, Fe, NO3−, Pb, SO42−) (p < 0.05) relative to the tailings dam. Groundwater did not pose non-carcinogenic risk due to studied trace elements. However, arsenic had the potential to cause medium to high cancer risk to the local population. We propose re-vegetation of the tailings dam, diversion of surface tailings drainage to a containment pond and the provision of continuous piped water supplies.

Spatial mapping of groundwater quality in the municipality of Santa Ignacia, Tarlac, Philippines

The municipality of Santa Ignacia in the Province of Tarlac is highly dependent on groundwater as its major water supply for various purposes, but there is inconsistency in monitoring groundwater quality in the area which may impact the health of consumers. This study presented the preliminary assessment of groundwater quality through the application of spatial mapping. Out of 6,815 wells in the municipality, groundwater samples were collected from 274 hand pump wells. The measurements of selected groundwater quality parameters such as pH, conductivity, nitrate, nitrite, and iron of groundwater samples were determined on-site. The geographical coordinates of sampled wells and measurements of groundwater quality parameters were used in Geographic Information System software, QGIS, to construct the spatial distribution and spatial variation maps. The values of measured parameters were interpolated using the inverse distance weighted technique to predict the parameters at other sites in Santa Ignacia. Spatial variation maps revealed that the groundwater quality parameters varied in the municipality. All measured parameters, except the nitrite content, were within the acceptable limits set by the World Health Organization for drinking water. The high level of nitrite content in groundwater may be attributed to the application of fertilizers during agricultural activities. The nitrite content of groundwater, which exceeded the permissible limit, may cause long-term public health problems. Hence, an upscale evaluation and monitoring of groundwater quality and existing anthropological activities in the municipality are highly recommended. The identification of other possible source(s) of nitrite is necessary to lessen possible contamination risk and to protect the groundwater sources in the municipality. The results of this preliminary study would be useful in prospect studies of groundwater quality in the study area and in other provinces in the Philippines.

GIS-based spatio-temporal and geostatistical analysis of groundwater parameters of Lahore region Pakistan and their source characterization

Assessment of groundwater quality is critical, especially in the areas where it is continuously deteriorating due to unplanned industrial growth. This study utilizes GIS-based spatio-temporal and geostatistical tools to characterize the groundwater quality parameters of Lahore region. For this purpose, a large data set of the groundwater quality parameters (for a period of 2005–2016) was obtained from the deep unconfined aquifers. GIS-based water quality index (WQI) and entropy water quality index (EWQI) models were prepared using 15 water quality parameters pH (power of hydrogen), TDS (Total dissolve solids), EC (Electrical conductivity), TH (Total hardness), Ca2+ (Calcium), Mg2+ (Magnesium), Na+ (Sodium), K+ (Potassium), Cl− (Chloride), As (Arsenic), F (Fluoride), Fe (Iron), HCO3– (Bicarbonate), NO3− (Nitrate), and SO42− (Sulfate). The data analysis exhibits that 12% of the groundwater samples fell within the category of poor quality that helped to identify the permanent epicenters of deteriorating water quality index in the study area. As per the entropy theory, Fe, NO3−, K, F, SO42− and As, are the major physicochemical parameters that influence groundwater quality. The spatio-temporal analysis of the large data set revealed an extreme behavior in pH values along the Hudiara drain, and overall high arsenic concentration levels in most of the study area. The geochemical analysis shows that the groundwater chemistry is strongly influence by subsurface soil water interaction. The research highlights the significance of using GIS-based spatio-temporal and geostatistical tools to analyze the large data sets of physicochemical parameters at regional level for the detailed source characterization studies.

Physical\u2013chemical evaluation of groundwater quality in semi-arid areas: case study\u2014Sabzevar plain, Iran

Groundwater is one of the most important water sources in arid and semi-arid areas. With the increasing world population and the water demand for agriculture and urban use, the need for water resources has increased, especially in arid and semi-arid regions, where groundwater resources play a significant role. To prevent the pollution of groundwater resources, various studies for their preservation and maintenance should be carried out, including a detailed plan for proper management of water resources and establishing a balance between water quality and how to use them. It becomes important to understand the spatial change of the quality of groundwater resources. In this study, Sabzevar plain, a typical region of semi-arid climate in Iran, was selected as a case study to assess the groundwater quality of the region, using data from 24 observation wells between 2015 and 2019. Using Arc GIS software, a map of groundwater quality parameters in the study area was prepared for quality assessment and comparison with existing international standards. The results showed that (except pH and HCO3−) the concentration of Sodium, Magnesium, and other anions and cations is higher than the corresponding WHO standard limit, suggesting that the study area is unsuitable for drinking and agricultural use. According to the Wilcox chart, 87.5% of the samples are in the C4S4 class while 8.33% are in the C4S3 class, showing the groundwater unsuitable for agricultural use due to its high salinity and alkalinity. Piper diagrams show that more than 50% of the samples are non-carbonate alkalis, indicating a very high salinity in the area. According to the pie chart, chlorine ion and sodium ion are the dominant anions and cations in the Sabzevar plain, respectively. The Schuler diagram shows that none of the samples examined were in a good class for drinking. Therefore, considering the importance of water for agricultural activities in the study area, it is recommended to have agricultural management solutions to prevent groundwater mixing with freshwater resources.

TEMPORAL VARIATION OF GROUNDWATER QUALITY IN SLEMAN, YOGYAKARTA, INDONESIA

Groundwater quality evaluation is important to gain an insight of contamination source. It can later be utilized to review the implementation of a water resource management policy in a specific region. Aim: This study evaluate the short-term temporal variation of groundwater quality and its possible contamination source in Sleman, Yogyakarta. Methodology and Results: the statistical approach was utilized using boxplot, principle component analysis (PCA) and correlation matrices, to the data for 50 sampling sites. The data of groundwater quality are available from the local environmental authority of Environmental Agency Sleman.The box plots revealed that groundwater quality might largely influenced by rainfall in the area. The factor loading of PCA presented that the ratio of concentration of both chloride and TDS are the most varied of all samples, and the less variable parameter is fluoride. The pair of groundwater quality parameter which had strong correlation were varied in each year, except for TDS and chloride that showed strong correlation in all three years. Nitrite had strong correlation with iron in 2017 and, nitrite also had strong correlation with both manganese and fluoride in 2019. The existence of fluoride in correlation with other parameter might give an insight of contamination from livestock wastes, where in the study area there are many poultry and cow farms, and small scale chicken slaughter industries. Conclusion, significant and impact study: This study gives preliminary understanding on temporal variation of groundwater quality, for further research on groundwater quality in Sleman, Yogyakarta.

Spatial Evaluation of Groundwater Quality Using GIS and WQI in Gadilam River Basin, Tamil Nadu, India


 
 
 The aims of the current research are to assess the drinking water quality of the groundwater in the Gadilam River Basin, which is located in the northern part of Tamil Nadu, by identifying the groundwater quality index and examine its suitability for drinking. The current work determines the levels of groundwater quality parameters based on 120 groundwater samples; 50 samples from Archaean formation, 34 samples from Quaternary formation, 35 samples from Tertiary formation and the remaining sample from Cretaceous formation. Additionally, this research compares the determined levels with the various standards for drinking. Furthermore, the variability of parameters of the groundwater quality is explored in this paper by using the spatial interpolation method. The conclusion of this research reveals that the groundwater quality parameters such as Calcium (Ca2+), Magnesium (Mg2+), Nitrate (NO32-), Fluoride (F-), Sulphate (SO42-), Bi-carbonate (HCO3-) and Percentage of Hydrogen (pH) values are observed to be within the limiting value for WHO 2017 in all the formations during the seasons in which they were taken. The water quality index (WQI) values of the Archaean, Quaternary and Tertiary formations are found to be less than 100 meq/L in all stations in both seasons. In order of WQI, these stations come under the category of “Excellent” and “Good”. The Piper trilinear classification of groundwater samples fall in the field of mixed Ca-Mg-Cl, and No dominance, some of the samples represent Na-K, Cl types of water.
 
 

Natural and Anthropogenic Controls of Groundwater Quality in Sri Lanka: Implications for Chronic Kidney Disease of Unknown Etiology (CKDu)

Poor groundwater quality in household wells is hypothesized as being a potential contributor to chronic kidney disease of unknown etiology (CKDu) in Sri Lanka. However, the influencing factors of groundwater quality in Sri Lanka are rarely investigated at a national scale. Here, the spatial characteristics of groundwater geochemistry in Sri Lanka were described. The relationships of groundwater quality parameters with environmental factors, including lithology, land use, and climatic conditions, were further examined to identify the natural and anthropogenic controlling factors of groundwater quality in Sri Lanka. The results showed that groundwater geochemistry in Sri Lanka exhibited significant spatial heterogeneity. The high concentrations of NO3− were found in the districts that have a higher percentage of agricultural lands, especially in the regions in the coastal zone. Higher hardness and fluoride in groundwater were mainly observed in the dry zone. The concentrations of trace elements such as Cd, Pb, Cu, and Cr of all the samples were lower than the World Health Organization guideline values, while some the samples had higher As and Al concentrations above the guideline values. Principal component analysis identified four components that explained 73.2% of the total data variance, and the first component with high loadings of NO3−, hardness, As, and Cr suggested the effects of agricultural activities, while other components were primarily attributed to natural sources and processes. Further analyses found that water hardness, fluoride and As concentration had positive correlations with precipitation and negative correlations with air temperature. The concentration of NO3− and water hardness were positively correlated with agricultural lands, while As concentration was positively correlated with unconsolidated sediments. The environmental factors can account for 58% of the spatial variation in the overall groundwater geochemistry indicated by the results of redundancy analysis. The groundwater quality data in this study cannot identify whether groundwater quality is related to the occurrence of CKDu. However, these findings identify the coupled controls of lithology, land use, and climate on groundwater quality in Sri Lanka. Future research should be effectively designed to clarify the synergistic effect of different chemical constituents on CKDu.

Analysis of temporal trend of groundwater quality using nonparametric Mann-Kendall and Sen’s methods (Case study: Yazd-Ardakan Plain)

Groundwater is the most important water resource for agriculture, industry, and drinking, and therefore qualitative changes in program planning and sustainable management of water resources are necessary. This study aimed to evaluate the trend of groundwater quality parameters of some selected stations in Yazd province by using non-parametric Mann-Kendall and Sens Methods. For this purpose, the water quality data were gathered in 25 stations of Yazd-Ardakan plain during 2005-2014. The quality parameters used in this study were TH, Cl-, K+, Mg++, Ca++, Na%, TDS, SAR, Na+, HCO3-, SO42-, EC, pH, the total sum of cation and anion. Before analyzing the data, the effect of significant first-order autocorrelation was investigated from the data set. The results showed most water quality parameters tend to rise. 50.8% and 49.2% of groundwater quality time series show meaningful positive trends during wet and dry seasons, respectively. Also, 54.7% and 45.3% of groundwater quality time series show meaningful negative trends during wet and dry seasons, respectively. Due to the positive slope of the trend line for most quality parameters, water quality in this region tends to decreases. The maximum positive slope of the trend line belongs to EC, where observed downstream of the plain. The loss of groundwater level due to an increase in consumption can be one of the main reasons for decreasing the groundwater quality and salinity.

GIS-based modelling of climate variability impacts on groundwater quality: Cape Flats aquifer, Cape Town, South Africa

The need to improve groundwater security remains critical, especially in urban areas where demand for groundwater as an alternative source of water supply is increasing following unprecedented population growth. Climate change continues to threaten groundwater resources in such areas. This study assessed and analysed data from a variety of sources that required holistic analytical tools to demonstrate the impacts of climate change on groundwater quality at the local level. We evaluated how climate conditions affect groundwater quality using a hydrological model (WaterWorld model) in a GIS context. The Cape Flats Aquifer in the city of Cape Town in South Africa was chosen as a case study. The WaterWorld model was used to calculate hydrologic scenarios based on climate change factors and groundwater quality parameters for the period 1950–2000. Mean annual precipitation and temperature were simulated using the multi-model mean and Representative Concentration Pathway 8.5 for the years 2041–2060. Simulation results showed that annual precipitation will increase until 2041 and then decrease until 2060. A significant temperature increase of 1.9 °C–2.3 °C was predicted. Water balance simulations showed a decrease of about 8.6% per year under the future dry climate. ArcGIS 10.3 was used to combine geospatial data and develop a groundwater vulnerability map. Modelling analysis based on GIS showed that the southern and central suburbs of the study area are more susceptible to groundwater contamination and have high surface runoff and higher average temperatures. The groundwater vulnerability index and electrical conductivity concentrations showed a strong positive correlation when the model was validated using linear regression analysis (R2 = 0.99, P < 0.05). In this article, we recommend the use of the WaterWorld model in a GIS environment to simulate hydrologic scenarios on climate change and groundwater quality parameters to provide practical and feasible insights for actions to improve groundwater management.

Reliability evaluation of groundwater quality index using data-driven models.

A trustworthy evaluation of the groundwater quality situations for different usages (i.e., drinking, industry, and agriculture) can definitely improve the management of groundwater resources for quality and quantity control, particularly in the arid and semi-arid districts. In the present investigation, GQI values and their typical categories have been yielded by the World Health Organization (WHO) instruction for the Rafsanjan Plain, the central part of Iran, during a 15-year period beginning in 2002. In this study, four robust Data-Driven Techniques (DDTs) based on the evolutionary algorithms and classification concepts have been applied to present formulations for the prediction of groundwater quality index (GQI) values in the case study of Rafsanjan Plain. In this way, monthly groundwater quality parameters (i.e., electrical conductivity, total hardness, total dissolved solid, pH, chloride, bicarbonate, sulfate, phosphate, calcium, magnesium, potassium, and sodium) were taken from 1349 observations. Performance of DDTs indicated that the Evolutionary Polynomial Regression (EPR) demonstrated the most accurate predictions of GQI than a model tree (MT), gene-expression programming (GEP), and Multivariate Adaptive Regression Spline (MARS). Moreover, to investigate all probable uncertainty in the values of groundwater quality parameters for the Rafsanjan Plain, a reliability-based probabilistic model was designed to assess the values of GQI. Hence, the Monte-Carlo scenario sampling technique has been quantified to evaluate the limit state function from DDTs. Moreover, there is a high probability (almost 100%) for the whole region to pass the "Excellent" quality, but it reduces to almost 50% over the "Good" and leads to almost 0% for the "Poor" quality.

Iran's Groundwater Hydrochemistry

AbstractIran's groundwater hydrochemistry has not been well understood. In this study, Iran's groundwater hydrochemistry is evaluated using a rich, ground‐trusted data sampled from 9,468 wells distributed across the country in 2011. Twelve groundwater quality parameters were analyzed in each sample, resulting in 113,616 parameters over the study period. Examination of anions‐cations shows that concentrations of sodium, calcium, chloride, and sulphate are higher than the acceptable threshold for drinking‐use suggested by the World Health Organization in about 40%, 21%, 25%, and 20% of the samples, respectively. The results of the water quality index reveal that most of the groundwater resources in the central, southern and eastern regions of Iran, which supply the majority of the domestic water for populated cities, do not meet the requirements for drinking‐use. Although the groundwater in northern parts fulfills the requirements for irrigation‐use, it is only suitable for irrigation of salinity‐friendly crops in central, eastern and southern regions. Ionic types and hydrochemistry facies indicate the dominance of mix water type in 13 out of 30 of Iran's sub‐basins, followed by sodium‐chloride water type in nine sub‐basins. Local geology and lithology are mainly attributed to the distribution of groundwater facies in Iran. In general, our findings reveal a distinctive relationship between Iran's geological‐geomorphological features and hydrochemical facies/groundwater quality. The findings can be used in the formulation of new strategies and policies for Iran's groundwater quality management in the future.

Dinamika hidrokimia air tanah pada Akuifer Pasiran Pulau Yeben Raja Ampat, Papua Barat

The quality of coastal ground water on small islands has characteristics that are influenced by environmental and area factors. Yeben Island is a small island with an area of 0.57 km2 with priority coastal and marine tourism areas in the islands of Raja Ampat. This study aims to (1) analyze levels of ground water quality parameters and (2) analyze water samples against water quality standards. Groundwater samples taken as many as 4 samples from the study location. The location of water samples is in the morphology of the coastal plain. The analysis of each physical and chemical parameter of each groundwater sample is carried out by comparing the value of drinking water quality standards. The results are presented in a comparison table of quality standards and a graph of scaled values.Based on the results, the laboratory shows that it exceeds the quality standard of physical elements and chemical elements including fluoride, hardness, sulfate and organic substances. In general, the quality of water is poor. Poor ground water quality occurs due to the influence of sea water intrusion.

Characterization of Ground Water Quality in Southern and Northern Region of Zanzibar Island

Millions of people from different countries depend on groundwater, which might contain elevated levels of unhygienic constituents. Poor quality of drinking water in many countries has been forcing people to use bottled water. In the present study, groundwater samples were collected in November 2014 leading to twenty-nine analysis of groundwater samples. The primary objective of this paper is to study the selected groundwater quality parameters as an establishment of preliminary baselines on groundwater constituents. A total of twenty nine water samples were collected (fourteen and fifteen samples from North and South regions of Zanzibar Island respectively. Physical parameters (Turbidity, oxidation-reduction potential ORP, Eh, pH, total dissolved soild TDS, salinity, and Electrical conductivity (EC) were determined in situ using Horiba multiparameters digital meters. Analysis of anions (NO3-, Br- , SO42-, F-, NO2-) was carried out using Ion chromatography (IC). Nitrite and nitrate for some water were below detection limit (BDL) The order of relative abundance for anions in samples collected at Northern region of Zanzibar Island, was NO3- &gt; Br- &gt; SO42- &gt; F- &gt; NO2- , while for the Southern region the order was NO3- &gt;Br- &gt; NO2- &gt; SO42- &gt; F- . In both regions, the orders for other parameters were; Turbidity &gt; pH &gt; salinity; and EC &gt;TDS &gt; ORP &gt; Eh. Almost all the measured parameters were within the WHO guidelines for drinking water. However, for nitrate and bromide, the percentage that exceeded the WHO limit was 7%, and 10.3% respectively. Based on toxicological perspective, although few samples had concentrations above groundwater quality criterion it is fundamental to estimate the intake by humans through the drinking water pathways.