Identification of influencing factors for groundwater quality variation using multivariate analysis

This paper reports the results of multivariate analysis on the major-ions data present in groundwater collected in a hydrogeochemical survey of a hard rock terrain in Andhra Pradesh, India. The use of factor analysis is proposed, as a first step, for identifying the processes influencing the hydrogeochemical variations in groundwater. As a result of the application factor analysis, three factors were obtained, which explained characterization of groundwater quality and identified the sources for the presence of ions and its variations in concentrations and their geochemical processes. The natural dissolution of existing rocks of granites and granitic gneisses is the common influencing source for its hydrogeochemical character in the study area, but at some localized zones, the human-influenced sources of agricultural, industrial and urbanization are the dominating factors. The spatial and seasonal variation of the hydrogeochemical processes associated with the factor variables in the groundwater quality of the study area were analysed and evaluated.     

Spatial and statistical assessment of nitrate contamination in groundwater:Case of Sais Basin,Morocco

The objective of this study is to evaluate the nitrate contamination in the plioquaternary aquifer of Sais Basin based on a statistical approach. A total of 98 samples were collected in the cultivated area during the spring and autumn period of 2018. The results show that 55% and 57% of the samples in spring and autumn respectively exceed the threshold fixed by WHO(50 mg/L). However, nitrate concentrations do not show seasonal and spatial variation(p0.05). The results of the correlation matrix, principal component analysis(PCA), and hierarchical cluster analysis(HCA) suggest that nitrate pollution is related to anthropogenic source. Moreover, multiple linear regression results show that NO_3 is more positively explained in the spring period by Ca and SO_4 and negatively explained by pH and HCO_3. Regarding the autumn period, nitrate pollution is positively explained by Ca and negatively by pH. This study proposes a useful statistical platform for assessing nitrate pollution in groundwater.     

Assessment of groundwater quality using multivariate statistical techniques in Hashtgerd Plain, Iran

Multivariate statistical techniques, such as cluster analysis (CA), factor analysis (FA), principal component analysis (PCA), and discriminant analysis (DA), were applied for the evaluation of variations and the interpretation of a large complex groundwater quality data set of the Hashtgerd Plain. In view of this, 13 parameters were measured in groundwater of 26 different wells for two periods. Hierarchical CA grouped the 26 sampling sites into two clusters based on the similarity of groundwater quality characteristics. FA based on PCA, was applied to the data sets of the two different groups obtained from CA, and resulted in three and five effective factors explaining 79.56 and 81.57% of the total variance in groundwater quality data sets of the two clusters, respectively. The main factors obtained from FA indicate that the parameters influencing groundwater quality are mainly related to natural (dissolution of soil and rock), point source (domestic wastewater) and non-point source pollution (agriculture and orchard practices) in the sampling sites of Hashtgerd Plain. DA provided an important data reduction as it uses only three parameters, i.e., electrical conductivity (EC), magnesium (Mg²⁺) and pH, affording more than 98% correct assignations, to discriminate between the two clusters of groundwater wells in the plain. Overall, the results of this study present the effectiveness of the combined use of multivariate statistical techniques for interpretation and reduction of a large data set and for identification of sources for effective groundwater quality management.     

Influence of Sungun copper mine on groundwater quality,NW Iran

Sungun mine is the largest open-cast copper mine in northwest of Iran and is in the primary stages of extraction. The influence of mining activity on the quality of regional groundwater has been taken in to consideration in this study. Accordingly, sampling was done from 22 springs in the study area. The concentrations of major anions and cations as well as Al, Cu, Cd, Cr, Fe, Mn, and Zn were determined for all 22 spring samples in mid-August 2005. The results showed that the concentrations of most of these elements were below the USA Environmental Protection Agency (EPA) limits; however, Al and Fe concentrations are considered to be more than limits in a couple of samples. Despite the fact that geological formations are highly weathered and fractured, the dissolution of minerals within the study area is low. This may be justified by the relatively high alkalinity of local underground water which keeps metals in solid phase and does not let them enter dissolved phase. Additionally, this may be attributed to the high velocity of groundwater flows, which do not give enough time for minerals to dissolve. Correlation coefficients among water chemistry components were determined and the weighted-pair group method was chosen for cluster analysis. Accordingly, high correlation among Al, Fe and Cr, Cd ,and Cu, sodium absorption ratio (SAR) and Na as well as total hardness (TH), Ca, and Mg were observed. The chemical characteristics of water compositions on the basis of major ion concentrations were evaluated on a Schoeller and Piper diagram. Accordingly, the dominant type of water in the region is considered to be Ca-HCO₃ (calcium-bicarbonate type). However, this type of water is also rich in Na, K, and especially Mg. Regarding Schoeller diagram, the current status of local underground water is good for drinking purposes. By commencing mining excavation with designed capacity in near future, the minerals will come into contact with air and water resulting in dissolution, especially in ponds, which, in turn, will increase the concentration of toxic metals in groundwater. Considering future uses of this water including for drinking, irrigation, industrial purposes, etc., precautions must be taken in to consideration.     

Spatial analysis of groundwater quality for drinking purpose in Sirjan Plain,Iran by fuzzy logic in GIS

At present,due to shortage of water resources,especially in arid and semiarid areas of the world such as Iran,exploitation of groundwater resources with suitable quality for drinking is of high importance.In this regard,contamination of groundwater resources to heavy metals,especially arsenic,is one of the most important hazards that threaten human health.The present study aims to develop an approach for presenting the groundwater quality of Sirjan city in Kerman Province,based on modern tools of spatial zoning in the GIS environment and a fuzzy approach of evaluating drinking water in accordance with the standards of world health organization(WHO).For this purpose,qualitative data related to 22 exploitation wells recorded during 2002 to 2017 were used.In addition,fuzzy aggregate maps were prepared in two scenarios by neglecting and considering arsenic presence in groundwater resources.The results showed a decrease in groundwater quality over time.More specifically,neglecting the presence of arsenic,in 2002,all drinking wells in the area were located in an excellent zone,while in 2017 a number of operation wells were located in the good and medium zone.Also,the final map,considering the presence of arsenic as a limiting factor of drinking water,indicated that parts of the southern regions of the plain would be the best place to dig wells for drinking water.Therefore,the use of new methods can contribute significantly to the usage of groundwater aquifers and provide a good view of the aquifer water quality.     

Geochemical assessment of groundwater quality in vicinity of Bhalswa landfill,Delhi, India,using graphical and multivariate statistical methods

A geochemical assessment of groundwater quality and possible contamination in the vicinity of the Bhalswa landfill site was carried out by using a hydrochemical approach with graphical and multivariate statistical methods with the objective of identifying the occurrence of various geochemical processes and understanding the impact of landfill leachates on groundwater quality. Results indicate that nitrate, fluoride and heavy-metal pollution are in an alarming state with respect to the use of groundwater for drinking purposes. Various graphical plots and statistical analyses have been applied to the chemical data based on the ionic constituents, water types, and hydrochemical facies to infer the impact of the landfill on groundwater quality. The statistical analysis and spatial and temporal variations indicate the leaching of contaminants from the landfill to the groundwater aquifer system. The concentrations of heavy metals in the landfill leachates are as follows: Fe (22 mg/l), Mn (~20 mg/l), Cu (~10 mg/l), Pb (~2 mg/l), Ni (0.25 mg/l), Zn (~10 mg/l), Cd (~0.2 mg/l), Cl⁻ (~4,000 mg/l), SO₄²⁻ (~3,320 mg/l), PO₄³⁻ (~4 mg/l), NO₃⁻ (30 mg/l) and fluoride (~50 mg/l); all were much higher than the standards. The study reveals that the landfill is in a depleted phase and is affecting groundwater quality in its vicinity and the surrounding area due to leaching of contaminants.     

Water pollution sources assessment by multivariate statistical methods in the Tahtali Basin,Turkey

In this study, multivariate statistical methods including factor, principal component and cluster analysis were applied to surface water quality data sets obtained from the Tahtali River Basin, Turkey. Factor and principal components analysis results revealed that surface water quality was mainly controlled by agricultural uses and domestic discharges. Cluster analysis generated two clusters. Based on the locations of the sites consisted by each cluster and variable concentrations at these stations, it was concluded that agricultural discharges strongly affected north and northeast part of the region. These methods are believed to assist water managers to understand complex nature of water quality issues and determine priorities to improve water quality.     

Distribution of fluoride in groundwater of Maku area, northwest of Iran

High fluoride groundwater occurs in Maku area, in the north of West Azarbaijan province, northwest of Iran. Groundwater is the main source of drinking water for the area residents. Groundwater samples were collected from 72 selected points including 40 basaltic and 32 nonbasaltic springs and wells, in two stages, during June and August 2006. The areas with high fluoride concentrations have been identified, and the possible causes for its variation have been investigated. Regional hydrogeochemical investigation indicates that water-rock interaction is probably the main reason for the high concentration of ions in groundwater. The concentration of F⁻ in groundwater is positively correlated with that of HCO₃ ⁻ and Na⁺, indicating that groundwater with high HCO₃ ⁻ and Na⁺ concentrations help to dissolve some fluoride-rich minerals. All of the water samples, collected from the basaltic areas do not meet the water quality standards for fluoride concentration and some other parameters. Hence, it is not suitable for consumption without any prior treatment. Inhabitants of the area that obtain their drinking water supplies from basaltic springs and wells are suffering from dental fluorosis. The population of the study area is at a high risk due to excessive fluoride intake especially when they are unaware of the amount of fluoride being ingested due to lack of awareness.     

地下水中有机污染物分析质量控制研究

建立了水中96种有机化合物的分析配套方案,包括吹扫捕集-气相色谱质谱法测定水中挥发性有机化合物,气相色谱火焰光度检测器测定水中有机磷农药,气相色谱电子捕获检测器测定水中有机氯农药和多氯联苯,高效液相色谱二极管阵列-荧光检测器联用测定水中多环芳烃。方法检出限满足中国地质调查局《地下水污染调查评价规范》的要求。同时对样品测试中质量控制方法进行研究,制定了一套行之有效的质量控制方案,质量控制结果满意。     

Spatial distribution,pollution characterization and health risk assessment of selected metals in groundwater of Lahore,Pakistan

Groundwater pollution is a major global environmental issue especially in the large cities and trace metals are considered as most important aquatic pollutants. The present study is based on the measurement and characterization of various physicochemical parameters (pH, EC, TDS, DO, alkalinity, hardness, and chloride), major cations (Ca, Mg, Na and K) and selected trace metals (Sr, Li, Fe, Zn, Cu, Co, Mn, Ag, Cd, Cr, Ni, and Pb) in the groundwater of Lahore, Pakistan during summer and winter (2017–18) seasons. Groundwater is the main source of drinking water in urban areas of Lahore. Seasonal comparison of the data indicated that majority of the metals showed relatively higher concentrations during winter than summer. Most of the metals exhibited significant spatial variability during both seasons; relatively higher metal levels were found in the old settlements and thickly populated areas of the city. Average concentrations of Pb, Ni, Cd and Co in the groundwater were found to be higher than the national and international guideline values. Factor analysis and cluster analysis revealed major anthropogenic contributions of Ni, Co, Cd, Cu, Cr and Pb in the groundwater while rest of the metals showed mixed and/or natural contributions. Evaluation of human health risks for the metal contents in groundwater revealed that Pb, Co, Ni and Cd were associated with significantly higher non-carcinogenic risks (HQ_ing > 1); the calculated risk for children was considerably higher than the adults. Moreover, the carcinogenic risk associated with Ni, Cr, Cd and Pb exceeded the safe limits. The present study revealed significantly higher anthropic pollutants in the groundwater which imposed considerable risks to human; therefore, it is recommended to implement immediate remedial measures to ensure safe drinking water.     

Salinization of groundwater in arid and semi-arid zones: an example from Tajarak,western Iran

Study of the groundwater samples from Tajarak area, western Iran, was carried out in order to assess their chemical compositions and suitability for agricultural purposes. All of the groundwaters are grouped into two categories: relatively low mineralized of Ca–HCO₃ and Na–HCO₃ types and high mineralized waters of Na–SO₄ and Na–Cl types. The chemical evolution of groundwater is primarily controlled by water–rock interactions mainly weathering of aluminosilicates, dissolution of carbonate minerals and cation exchange reactions. Calculated values of pCO₂ for the groundwater samples range from 2.34 × 10⁻⁴ to 1.07 × 10⁻¹ with a mean value of 1.41 × 10⁻² (atm), which is above the pCO₂ of the earth’s atmosphere (10^−3.5). The groundwater is oversaturated with respect to calcite, aragonite and dolomite and undersaturated with respect to gypsum, anhydrite and halite. According to the EC and SAR the most dominant classes (C3-S1, C4-S1 and C4-S2) were found. With respect to adjusted SAR (adj SAR), the sodium (Na⁺) content in 90% of water samples in group A is regarded as low and can be used for irrigation in almost all soils with little danger of the development of harmful levels of exchangeable Na⁺, while in 40 and 37% of water samples in group B the intensity of problem is moderate and high, respectively. Such water, when used for irrigation will lead to cation exchange and Na⁺ is adsorbed on clay minerals while calcium (Ca²⁺) and magnesium (Mg²⁺) are released to the liquid phase. The salinity hazard is regarded as medium to high and special management for salinity control is required. Thus, the water quality for irrigation is low, providing the necessary drainage to avoid the build-up of toxic salt concentrations.     

Spatial assessment and redesign of a groundwater quality monitoring network using entropy theory, Gaza Strip, Palestine

Using entropy theory, a methodology was developed for the evaluation and redesign of groundwater quality monitoring wells in the Gaza Strip in Palestine. Essential to the methodology is the development of a Transinformation Model (TM) which yields the amount of information transfer and the dependency between the wells as a function of distance. The TM parameters, such as the minimum transinformation and the range, were employed for evaluating the network which revealed that most of the distances between wells were less than the range. It also indicated that a high percentage of redundant information existed in the network. Therefore, the network was reduced by superimposing a square pattern over the monitored area and selecting one well per square block in a stratified pattern. The methodology was tested using the chloride data collected from 1972–2000 from 417 groundwater quality monitoring wells in the Gaza Strip. The number of the groundwater quality monitoring wells in the Gaza Strip was reduced by 53%, while there was 26% redundant information based on the minimum existing distance between wells. This methodology is meant to help monitor the groundwater quality (salinity) in the Gaza Strip.     

Water quality assessment of the Jinshui River (China) using multivariate statistical techniques

Multivariate statistical techniques have been widely utilized to assess water quality and evaluate aquatic ecosystem health. In this study, cluster analysis, discriminant analysis, and factor analysis techniques are applied to analyze the physical and chemical variables in order to evaluate water quality of the Jinshui River, a water source area for an interbasin water transfer project of China. Cluster analysis classifies 12 sampling sites with 22 variables into three clusters reflecting the geo-setting and different pollution levels. Discriminant analysis confirms the three clusters with nine discriminant variables including water temperature, total dissolved solids, dissolved oxygen, pH, ammoniacal nitrogen, nitrate nitrogen, turbidity, bicarbonate, and potassium. Factor analysis extracts five varifactors explaining 90.01% of the total variance and representing chemical component, oxide-related process, natural weathering and decomposition processes, nutrient process, and physical processes, respectively. The study demonstrates the capacity of multivariate statistical techniques for water quality assessment and pollution factors/sources identification for sustainable watershed management.     

Analysis of the effect of geology, soil properties, and land use on groundwater quality using multivariate statistical and GIS methods

The regional survey of groundwater used as a small water supply system was performed to know the effect of geology, soil properties and land use on groundwater quality at Nonsan City, Korea. A total of 126 groundwater samples were collected and analyzed at the study area. The multivariate statistical methods, principal components analysis and discriminant analysis, and GIS technique were used for the quantitative interpretation of groundwater quality. The study area is mainly composed of Precambrian gneiss, Jurassic granite, and Cretaceous volcanics, and metasedimentary rocks of the Ogcheon zone. The land use was grouped as paddy, upland, grassland, resident, point source, industrial area, and water system. The soil properties were classified as 4 major groups, Entisols, Alfisols, Inceptisols, and Ultisols, by the degree of development, and reclassified as 11 subgroups. The modified and simplified geologic map, soil map, and land use map were made by using ARCGIS soft-ware. The area of geology, soil property, and land use affecting the groundwater quality for each well were also calculated by ARCGIS soft-ware to acquire the quantitative parameters for multivariate statistical analysis. The monitoring results of groundwater in the study area showed that 13%-21% of the groundwater samples exceeded the portable water guideline and the main causes were turbidity, bacteria, arsenic and nitrate-N. The spatial distribution of each component showed the close relationship between groundwater quality and geology reflecting the topography, land use.     

Characterization and evaluation of the factors affecting the geochemistry of groundwater in Neyveli,Tamil Nadu,India

In order to achieve a better understanding of the nature of the factors influencing ground water composition as well as to specify them quantitatively, multivariate statistical analysis (factor analysis) were performed on the hydrochemical data of this area. R-mode factor analysis was carried out on the geochemical results of the 79-groundwater samples and the factor scores were transferred to areal maps. Fundamental chemical parameters of the groundwater have been compounded together for characterizing and interpreting a few empirical hydrogeochemical factors controlling the chemical nature of water. R-mode factor analysis reveals that the groundwater chemistry of the study area reflects the influence of anthropogenic activities, silicate weathering reactions, precipitation, dissolution and subsequent percolation into the groundwater. The data have been put into few major factors and the seasonal variation in the chemistry of water has been clearly brought out by these factors. Factor scores were transferred to contour diagrams and the factor score analysis has been used successfully to delineate the stations under study with various factors and the seasonal effect on the sample stations.     

Geochemical evolution and quality assessment of water resources in the Sarcheshmeh copper mine area (Iran) using multivariate statistical techniques

Hydrochemical data were gathered throughout the last 12 years from 57 sampling stations in the drainage basin of the Sarcheshmeh copper mine, Kerman Province, Iran. The mean values of these data for each sampling station were used to evaluate water quality and to determine processes that control water chemistry. Principal component analyses specified the oxidation of sulfide minerals, dissolution of carbonate and sulfate minerals and weathering of silicate minerals as the principal processes responsible for the chemical composition of water in the study area. Q-mode cluster analysis revealed three main water groups. The first group had a Ca-HCO₃–SO₄ composition whereas the second and third groups had Ca–SO₄ and Ca–Mg–SO₄ composition, respectively. The results of this study clearly indicated the role of sulfide minerals oxidation and the buffering processes in the geochemical evolution of water in the Sarcheshmeh area. Due to these processes, extensive changes occurred in the chemical composition of water by passage through the mining area or waste and low-grade dumps, so that the fresh water of the peripheral area of the pit evolved to an acid water rich in sulfate and heavy metals at the outlet of the pit and in the seepages of waste and low-grade dumps.     

Integrating multivariate statistical analysis with GIS for geochemical assessment of groundwater quality in Shiwaliks of Punjab,India

The dependency of people on groundwater has increased in the past few decades due to tremendous increase in crop production, population and industrialization. Groundwater is the main source of irrigation in Shiwaliks of Punjab. In the present study the samples were collected from predetermined location as was located on satellite image on basis of spectral reflectance. Global positioning system was used to collect samples from specific locations. Principal components analysis (PCA) together with other factor analysis procedures consolidate a large number of observed variables into a smaller number of factors that can be more readily interpreted. In the present study, concentrations of different constituents were correlated based on underlying physical and chemical processes such as dissociation, ion exchange, weathering or carbonate equilibrium reactions. The PCA produced six significant components that explained 78% of the cumulative variance. The concentration of the few trace metals was found to be much higher indicating recharge due to precipitation as main transport mechanism of transport of heavy metals in groundwater which is also confirmed by PCA. Piper and other graphical methods were used to identify geochemical facies of groundwater samples and geochemical processes occurring in study area. The water in the study area has temporary hardness and is mainly of Ca–Mg–HCO₃ type.     

Optimization of the DRASTIC method for groundwater vulnerability assessment via the use of simple statistical methods and GIS

The assessment of groundwater vulnerability to pollution has proved to be an effective tool for the delineation of protection zones in areas affected by groundwater contamination due to intensive fertilizer applications. By modifying and optimizing the well known and widely used DRASTIC model it was possible to predict the intrinsic vulnerability to pollution as well as the groundwater pollution risk more accurately. This method incorporated the use of simple statistical and geostatistical techniques for the revision of the factor ratings and weightings of all the DRASTIC parameters under a GIS environment. The criterion for these modifications was the correlation coefficient of each parameter with the nitrates concentration in groundwater. On the basis of their statistical significance, some parameters were subtracted from the DRASTIC equation, while land use was considered as an additional DRASTIC parameter. Following the above-mentioned modifications, the correlation coefficient between groundwater pollution risk and nitrates concentration was considerably improved and rose to 33% higher than the original method. The model was applied to a part of Trifilia province, Greece, which is considered to be a typical Mediterranean region with readily available hydrogeological and hydrochemical data.

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Resumen La evaluación de vulnerabilidad del agua subterránea a la contaminación ha demostrado ser una herramienta efectiva para la delimitación de zonas de protección en áreas afectadas por contaminación de aguas subterráneas debido a aplicaciones intensivas de fertilizantes. Mediante la modificación y optimización del bien conocido y ampliamente utilizado modelo DRASTIC fue posible predecir la vulnerabilidad intrínseca a la contaminación así como el riesgo a la contaminación del agua subterránea con mayor precisión. Este método incorporó el uso de técnicas estadísticas y geoestadísticas simples para la revisión del pesaje y establecimiento de rangos de factores de todos los parámetros DRASTIC bajo un ambiente SIG. El criterio para estas modificaciones fue el coeficiente de correlación de cada parámetro con las concentraciones de nitraros en agua subterránea. En base al grado significativo estadístico algunos parámetros fueros sustraídos de la ecuación DRASTIC, mientras que se consideró el uso de la tierra como un parámetro adicional de DRASTIC. Siguiendo las modificaciones antes mencionadas se mejoró considerablemente el coeficiente de correlación entre el riesgo a la contaminación del agua subterránea y las concentraciones de nitratos incrementando en 33% su valor en relación al método original. El modelo se aplicó en una parte de la provincia Trifilia, Grecia, la cual se considera ser una región Mediterránea típica con datos hidroquímicos e hidrogeológicos fácilmente disponibles.

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Résumé L’évaluation de la vulnérabilité des eaux souterraines à la pollution a montré qu’elle est un outil efficace pour délimiter les zones de protection dans les zones affectées par la contamination des eaux souterraines due à l’utilisation intensive de fertilisants. En modifiant et optimisant le modèle DRASTIC, bien connu et souvent utilisé, il a été possible de prédire la vulnérabilité intrinsèque à la pollution, et de définir plus précisément le risque de pollution. Cette méthode incorpore l’utilisation de simples techniques statistiques et géostatistiques, pour la révision des facteurs d’estimation et de pondération de tous les paramètres de DRASTIC sous S.I.G. Le critère de ces modifications était le coefficient de corrélation de chaque paramètre avec la concentration en nitrates dans les eaux souterraines. Sur la base de leur signification statistique, certains paramètres ont été soustraits de l’équation DRASTIC. Suivant les modifications mentionnées ci-dessus, le coefficient de corrélation entre les concentrations en nitrate et le risque de pollution des eaux souterraines a été considérablement amélioré de 33% par rapport à la méthode originale. Le modèle a été appliqué sur une partie de la province de Trifilia en Grèce, qui est considérée comme une région typiquement méditerranéenne avec des données hydrogéologiques et hydrochimiques aisément accessibles.

     

Geochemistry and quality assessment of groundwater using graphical and multivariate statistical methods. A case study: Grombalia phreatic aquifer (Northeastern Tunisia)

The Grombalia coastal aquifer, situated in Northeastern Tunisia, is a water source for public, agricultural, and industrial supplies in the region. The overexploitation of this aquifer, since 1959, and the agriculture activities led to the degradation, by places, of the water quality. The present study implemented graphical, modeling, and multivariate statistical tools to investigate natural and anthropogenic processes controlling Grombalia groundwater mineralization and water quality for promoting sustainable development. To attempt this goal, groundwater was collected from 33 observation wells in January 2004, and samples were analyzed for 10 physicochemical parameters (temperature, pH, salinity, Na⁺, Ca²⁺, K⁺, Mg²⁺, Cl^?, HCO^3?, and SO ₄ ^2? ). Hydrochemical facies using Piper diagram indicates a predominance of a mixed facies, of the Na-Cl-HCO₃ type, or Na-Ca-Cl-SO₄ type, and, with less expansion, Na Cl type. The main factors controlling Grombalia groundwater mineralization seem to be mineral dissolution of highly soluble salts especially, the halite dissolution existing in the surface salty deposits and, with less importance, the ion exchange and reverse ion exchange process with clay minerals existing in the aquifer. The comparison of the major ions of the Grombalia groundwater, with the World Health Organization norms of potability (WHO 2004), reveals that these waters cannot be used for human consumption without any treatment. Most waters of the Grombalia aquifer, with a relatively high salinity, are not suitable for irrigation, in ordinary conditions. Nevertheless, they can be used for permeable soils, with an adequate drainage and applying an excess of leaching water.