R-mod factor analysis, a popular multivariate statistical technique to evaluate water quality in Khaf-Sangan basin, Mashhad, Northeast of Iran

Water quality data are required in order to compare chemical water analyses and identify water masses. R-mode factor analysis, a popular multivariate statistical tool, has been effectively used for groundwater quality studies. In this paper, the R-mode factor analysis was applied to 50 groundwater samples collected from pumping wells in the Sangan-Khaf basin which is located in the southeast of Mashhad, northeast Iran. The groundwater samples were analysed for chemical parameters. The factor analysis was then performed on the chemical data set. It can be suggested that four factors in R-mode analysis explain more than 94.31% of the total variance. The contribution of each factor at sample points, factor score, was calculated. The spatial distribution of the factor scores for each factor was mapped separately. Since the Sangan iron mine south of the study area probably affects groundwater aquifer, therefore, such studies can be used to manage the groundwater quality in the study area.     

Geochemical factors controlling the chemical nature of water and sediments in the Gomti River, India

 R-mode factor analysis of the recently acquired data on water and sediment chemistry has been performed. Basic chemical parameters have been merged together which aid in interpreting a few empirical geochemical factors controlling the chemical nature of water and sediments of the Gomti River, a major Himalayan tributary of the Ganges drainage basin. Water chemistry seems to be controlled by three factors: bicarbonate, rainfall and silicate and phosphate factors. Sediment chemistry is largely controlled by the following four factors: clay, adsorption/desorption, Fe-Mn hydroxide and mercury factors. These factors show spatial and temporal variability in terms of their R-scores. Received: 8 September 1997 · Accepted: 15 December 1997     

Multivariate statistical analysis of geochemical data of groundwater in Veeranam catchment area,Tamil Nadu

The study of hydrogeochemistry of the Mio-Pliocene sedimentary rock aquifer system in Veeranam catchment area produced a large geochemical dataset. Groundwater samples were collected at 52 sites over 963.86 km² area and analyzed for major ions. The large number of data can lead to difficulties in the integration, interpretation and representation of the results. Two multivariate statistical methods, Hierarchical cluster analysis (HCA) and Factor analysis (FA), were applied to a subgroup of the dataset to evaluate their usefulness to classify the groundwater samples, and to identify geochemical processes controlling groundwater geochemistry. Hydrochemical data for 52 groundwater samples were subjected to Q- and R- mode factor and cluster analysis. R-mode analysis reveals the inter-relations among the variables studied and the Q-mode analysis reveals the inter-relations among the samples studied. The R-mode factor analysis shows that Ca, Mg and Cl with HCO₃ account for most of the electrical conductivity, total dissolved solids and total hardness of groundwater. The ‘single dominance’ nature of the majority of the factors in the R-mode analysis indicates non-mixing or partial mixing of different types of groundwater. Both Q-mode factor and Q-mode cluster analyses indicate an exchange between the river water and the groundwater in the vicinity. The rock water interaction like flood basin back swamp deposits of silty clayey formation is the major cause for the cluster II classification. Cluster classification map reveals that 58% of the study area comes under cluster II classification.     

Evaluation of the processes affecting vertical water chemistry in an alluvial aquifer of Mankyeong Watershed, Korea, using multivariate statistical analyses

Vertical variations of redox chemistry and groundwater quality were investigated in an alluvial aquifer beneath an agricultural area, in which deep groundwaters are free of NO₃, Fe, and Mn problems that are frequently encountered during the development of alluvial groundwaters. This study was performed to identify and evaluate vertical chemical processes attenuating these chemical species in the study area. For this study, the processes affecting groundwater chemistry were identified by factor analysis (FA) and the groundwater samples collected from six multilevel samplers were hierarchically classified into three different redox zones by cluster analysis (CA) based on the similarity of geochemical features. FA results indicated three major factors affecting the overall water chemistry: agricultural activities (factor 1), redox reactions (factor 2), and remnant seawater (factor 3). The groundwater quality in the study area was revealed to be controlled by a series of different redox reactions, resulting in different redox zones as a function of depth. It was also revealed that the low Fe and Mn levels in the groundwater of the deeper part are associated with sulfate reduction, which led to precipitation of Fe as iron sulfide and adsorption of Mn on it.     

Characterization of groundwater contamination using factor analysis

 The effluent contamination of groundwater at two industrial sites at Visakhapatnam, India, was studied using factor analysis. Thirty groundwater samples near a zinc smelter plant and 19 from the polymers plant were analyzed for specific conductance, chloride, bicarbonate, sulfate, calcium, magnesium, sodium, and potassium. The data were subjected to R-mode factor analysis and the factor scores transferred to areal maps. While magnesium and sulfate are the dominant contaminants at the zinc site, sodium, chloride, and bicarbonate from the effluent are affecting groundwater in the polymers area. Contour maps for each factor suggest the areal extension of the contaminants. Received: 1 March 1995 · Accepted: 18 September 1995     

Groundwater geochemistry of Ain Azel area,Algeria

Hydrogeochemical data for 18 groundwater samples and 11 hydrochemical parameters were subjected to Q- and R-mode cluster analysis and inverse geochemical modeling. Q-mode cluster analysis resulted in three distinct water types (brackish water type, saline water type and highly saline water type). R-mode cluster analysis led to the conclusion that the water–rock interaction is the major source of contamination for the groundwater in the area. Geochemical modeling results show that carbonates, gypsum, halite, carbon dioxide (gas), and chlorite are dissolving, whereas Ca-montmorillonite, gibbsite, illite, K-mica, kaolinite, and quartz are mostly precipitating along different flow paths in the groundwater system of the area.     

Groundwater components in the alluvial aquifer of the alpine Rhone River valley, Bois de Finges area, Wallis Canton, Switzerland

Source, type, and quantity of various components of groundwater, as well as their spatial and temporal variations were determined by different hydrochemical methods in the alluvial aquifer of the upper Rhone River valley, Bois de Finges, Wallis Canton, Switzerland. The methods used are hydrochemical modeling, stable-isotope analysis, and chemical analysis of surface water and groundwater. Sampling during high- and low-water periods determined the spatial distribution of the water chemistry, whereas monthly sampling over three years provided a basis for understanding seasonal variability. The physico-chemical parameters of the groundwater have spatial and seasonal variations. The groundwater chemical composition of the Rhone alluvial aquifer indicates a mixing of weakly mineralized Rhone River water and SO₄-rich water entering from the south side of the valley. Temporal changes in groundwater chemistry and in groundwater levels reflect the seasonal variations of the different contributors to groundwater recharge. The Rhone River recharges the alluvial aquifer only during the summer high-water period. Electronic Publication     

Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization

The study area is located in the southwestern part of Bangladesh. Twenty-six groundwater samples were collected from both shallow and deep tube wells ranging in depth from 20 to 60 m. Multivariate statistical analyses including factor analysis, cluster analysis and multidimensional scaling were applied to the hydrogeochemical data. The results show that a few factors adequately represent the traits that define water chemistry. The first factor of Fe and HCO₃ is strongly influenced by bacterial Fe (III) reduction which would raise both Fe and HCO₃ concentrations in water. Na, Cl, Ca, Mg and PO₄ are grouped under the second factor representing the salinity sources of waters. The third factor, represented by As, Mn, SO₄ and K is related to As mobilization processes. Cluster analysis has been applied for the interpretation of the groundwater quality data. Initially Piper methods have been employed to obtain a first idea on the water types in the study area. Hierarchical cluster analysis was carried out for further classification of water types in the study area. Twelve components, namely, pH, Fe, Mn, As, Ca, Mg, Na, K, HCO₃, Cl, SO₄ and NO₃ have been used for this purpose. With hierarchical clustering analysis the water samples have been classified into 3 clusters. They are very high, high and moderately As-enriched groundwater as well as groundwater with elevated SO₄.     

Multivariate statistical analyses of the groundwater system in Darb El-Arbaein, Southwestern Desert, Egypt

In Darb El-Arbaein, the groundwater is the only water resource. The aquifer system starts from Paleozoic–Mesozoic to Upper Cretaceous sandstone rocks. They overlay the basement rocks and the aquifer is confined. In the present research, the performance of the statistical analyses to classify groundwater samples depending on their chemical characters has been tested. The hydrogeological and hydrogeochemical data of 92 groundwater samples were obtained from the General Authority for Rehabilitation Projects and Agricultural Development authority in northern, central, and southern Darb El-Arbaein. A robust classification scheme for partitioning groundwater chemistry into homogeneous groups was an important tool for the characterization of Nubian sandstone aquifer. We test the performance of the many available graphical and statistical methodologies used to classify water samples. R-mode, Q-mode, correlation analysis, and principal component analysis were investigated. All the methods were discussed and compared as to their ability to cluster, ease of use, and ease of interpretation. The correlation investigation clarifies the relationship among the lithologic, hydrogeologic, and anthropogenic factors. Factor investigation revealed three factors, namely, the evaporation process–agricultural impact–lithogenic dissolution, the hydrogeological characteristics of the aquifer system, and the surface meteoric water that recharge the aquifer system. Two main clusters that subdivided into four subclusters were identified in the groundwater system based on hydrogeological and hydrogeochemical data. They reflect the impact of geomedia, hydrogeology, geographic position, and agricultural wastewater. The groundwater is undersaturated with respect to most selected minerals. The groundwater was supersaturated with respect to iron minerals in northern and southern Darb El-Arbaein. The partial pressure of the groundwater versus saturation index of calcite shows the gradual change in PCO₂ from atmospheric to the present aquifer pressures.     

Evaluation of hydrogeochemical characteristics of groundwater in parts of the lower Benue Trough, Nigeria

The aim of this work is to evaluate the hydrogeochemical characteristics of groundwater in parts of the lower Benue Through in Nigeria as well as to evaluate the variation in groundwater chemistry data and the suitability of the groundwater for drinking and other domestic purposes. This was based on chemical analyses of 44 water samples from existing wells and boreholes in the study area. From the statistical analysis (wide ranges, median and standard deviation), it is obvious that there are significant variations in the quality/composition of groundwater in the period of sampling. The calculated SAR, Na% and RSC values indicated that the water is of excellent to good quality and is suitable for irrigation. Na and HCO₃ are dominant with respect to the chemical composition of the groundwater. On the basis of water chemistry, hydrochemical indices and factor analysis the dominant controls or processes affecting the distribution of geochemical variables in the study area have been shown to be water/rock interaction which is mainly controlled by carbonate and silicate dissolution as well as anthropogenic influence to a lesser extent. Additional processes include cation exchange reactions and reverse ion exchange to a minor extent.     

Identification and evaluation of the hydrogeochemical processes of the lower part of Wadi Siham catchment area, Tihama plain, Yemen

One hundred forty-eight groundwater samples were collected from the lower part of Wadi Siham catchment area for hydrogeochemical investigations to understand the hydrogeochemical processes affecting groundwater chemistry and their relation with groundwater quality. Groundwater in the study area is abstracted from different aquifers. The study area is characterized by arid climate and extremely high relative humidity. The results indicate that groundwater in the study area is fresh to brackish in nature. The abundance of the major ions is as follows: Na⁺¹?>?Ca⁺²?>?Mg⁺²?≥?K⁺¹ and Cl^?1?>?HCO ₃ ^?1 ?>?SO ₄ ^?2 ?>?NO ₃ ^?1 . Various graphical and ionic ration plots, statistical analyses, and saturation indices calculations have been carried out using chemical data to deduce a hydrochemical evaluation of the study area. The prevailing hydrogeochemical processes operating in the study area are dissolution, mixing, evaporation, ion exchange, and weathering of silicate minerals in the eastern part (recharge areas). The reverse ion exchange and seawater intrusion control the groundwater chemistry along the Red Sea coast areas and few parts of the study area. Deterioration in groundwater quality from anthropogenic activities has resulted from saltwater intrusion along the coastal areas due to groundwater overpumping and extensive use of fertilizers and infiltration of sewage water. Salinity and nitrate contamination are the two major problems in the area, which is alarming considering the use of this water for drinking.     

罗山自然保护区地下水化学特征研究

罗山自然保护区是宁夏中部的水源涵养林区。通过对罗山地下水进行取样分析、综合运用描述性分析、因子分析的方法,对地下水化学成分的统计特征及其在空间上的变化规律进行了分析研究。结果表明:①罗山浅层地下水中HCO3-和SO42-绝对含量较高,为地下水中的主要离子。以罗山为中心,向四周辐射,地下水化学类型特征及演变规律;地下水中的Mg2+、Na+、Cl-、SO42-、NO3-和TDS的相关程度很高,主要是来自沉积砂岩、板岩中的长石、石英和绢云母;区内硫酸根离子、氯离子和水的总硬度普遍超标,咸水区对人体有害的氟化物含量超标,部分微咸水区的氟化物含量超标,淡水区未出现超标现象。     

Groundwater quality assessment using integrated geochemical methods,multivariate statistical analysis,and geostatistical technique in shallow coastal aquifer of Terengganu,Malaysia

Extensive agricultural, residential, and industrial activities have increased demand for water supplies, which can lead to groundwater quality degradation. The integration of geochemical methods, multivariate statistical analysis, and geostatistical approaches were carried out on 169 groundwater samples to elucidate the regional factors and processes that influencing the geochemical composition of groundwater in coastal shallow aquifer of Terengganu, Malaysia. Hydrochemical modelling revealed that the abundance of Ca and Mg was contributed by carbonate and silicate weathering while higher HCO₃ and Cl were resulted from reverse ion exchange reaction. Therefore, the dominant hydrogeochemical facies of groundwater was Ca-Mg-HCO₃-Cl type. The influence of salinization resulting from seawater mixing to the groundwater was corroborated by Cl/HCO₃ ratio, which affected around 50.9% of the groundwater samples slightly or moderately. Spatial mapping using ordinary kriging found that the threat of sea water intrusion is more prominent in the major river confluence especially around Terengganu and Marang River in the northeast and Dungun and Kemaman River confluence in southeast of study area. Moreover, factor analyses concluded that salinization, anthropogenic activities, reverse ion exchange, weathering processes, agricultural impact, and seasonal variations were the factors that regulate 63% of the major ion chemistry in study area. Finally, these findings showed the importance of understanding the hydrochemical characteristics for effective utilization, aquifer protection, and prediction of changes to minimize the effects of salinization and reduce human pollution such as agriculture and urbanization. It is essential steps in order to safeguard the utilization of groundwater resources for future generations.     

Hydrogeochemical evolution of groundwater in a Mediterranean coastal aquifer, Mersin-Erdemli basin (Turkey)

In this study, hydrogeologic and hydrochemical information from the Mersin-Erdemli groundwater system were integrated and used to determine the main factors and mechanisms controlling the chemistry of groundwaters in the area and anthropogenic factors presently affecting them. The PHREEQC geochemical modeling demonstrated that relatively few phases are required to derive water chemistry in the area. In a broad sense, the reactions responsible for the hydrochemical evolution in the area fall into four categories: (1) silicate weathering reactions; (2) dissolution of salts; (3) precipitation of calcite, amorphous silica and kaolinite; (4) ion exchange. As determined by multivariate statistical analysis, anthropogenic factors show seasonality in the area where most contaminated waters related to fertilizer and fungicide applications that occur during early summer season.     

Integrated hydrochemical assessment of the Quaternary alluvial aquifer of the Guadalquivir River, southern Spain

The alluvial aquifer of the Guadalquivir River comprises shallow Quaternary deposits located in the central-eastern part of the Province of Jaén in southern Spain, where groundwater resources are used mainly for crop irrigation in an important agricultural area. In order to establish the baseline hydrochemical conditions and processes determining the groundwater quality, groundwater and river water samples were collected as part of an integrated investigation that coupled multivariate statistical analysis with hydrochemical methods to identify and interpret the groundwater chemistry of the aquifer system. Three main hydrochemical types (Mg–Ca–HCO₃, Ca–Mg–SO₄–HCO₃–Cl and Na–Ca–Mg–Cl–SO₄) were identified. Further interpretation, using R-mode principal components analysis (PCA) conducted with 13 hydrochemical variables, identified two principal components which explain ⅔ of the variance in the original data. In combination with the hydrochemical interpretation, mineralogical analyses of the aquifer sediment together with inverse geochemical modelling using NETPATH showed that dedolomitization (calcite precipitation and dolomite dissolution driven by gypsum dissolution) is the principal hydrochemical process controlling the regional groundwater chemistry. Other processes such as silicate weathering, ion exchange, mixing between river water and groundwater, and agricultural practices also affect the groundwater chemistry.     

Origin of flooding water through hydrogeochemical identification,the Buenos Aires plain,Argentina

Hydrogeochemical behaviour of samples of surface and groundwater collected on a cross-section from Mendoza to the Buenos Aires provinces was studied based on chemical trends, mass balance and water mixing. Hydrogeochemical modelling included major, minor elements as well as stable isotopes (deuterium and 18-O). The area investigated is located in the “Médanos Longitudinales” (longitudinal dunes) of the northwest of Buenos Aires province, Argentina. The study area is subject to alternating flooding and drought. Rainfall and surface water subsequently transferred by rivers, canals and lagoons have been usually considered responsible for local flooding. For this study, origins of excess water were investigated using physical and chemical characteristics of the water involved. The prevalence of groundwater inflow to rainfall events was proposed based on data interpretation. Groundwater influence of flows of local and intermediate nature were defined and the importance of recharge, transit and discharge zones was highlighted. Lagoon floodwater, as well as groundwater from observation wells and production boreholes, show components of intermediate origin. Regional recharge water was identified in Mendoza and San Luis provinces. Their discharge zone was inferred to be located beyond the Buenos Aires province.     

Source and distribution of metals in urban soil of Bombay,India, using multivariate statistical techniques

Simplification of a complex system of geochemical variables obtained from the soils of an industrialized area of Bombay is attempted by means of R-mode factor analysis. Prior to factor analysis, discriminant analysis was carried out taking rock and soil chemical data to establish the anthropogenic contribution of metals in soil. Trace elements (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) are expressed in terms of three rotated factors. The factors mostly indicate anthropogenic sources of metals such as atmospheric fallout, emission from different industrial chimneys, crushing operations in quarries, and sewage sludges. Major elements (Na, Mg, Al, Si, P, K, Ca, Ti, Mn, and Fe) are also expressed in terms of three rotated factors indicating natural processes such as chemical weathering, presence of clay minerals, and contribution from sewage sludges and municipal refuse. Summary statistics (mean, standard deviation, skewness, and kurtosis) for the particle size distribution were interpreted as moderate dominance of fine particles. Mineralogical studies revealed the presence of montmorillonite, kaolinite, and illite types of clay minerals. Thus the present study provides information about the metal content entering into the soil and their level, sources, and distribution in the area.     

Groundwater classification using multivariate statistical methods: Southern Ghana

This study demonstrates the strength of R-mode factor analysis and Q-mode hierarchical cluster analysis in determining spatial groundwater salinity groups in southeastern Ghana. Three hundred and eighty three (383) groundwater samples were taken from six hydrogeological terrains and surface water bodies and analyzed for the concentrations of the major ions, electrical conductivity and pH. Q-mode hierarchical cluster analysis and R-mode factor analysis were respectively used to spatially classify groundwater samples and determine the probable sources of variation in groundwater salinity. The quality of groundwater for irrigation was then determined using three major indices. The analyses revealed two major sources of variation in groundwater salinity: silicate mineral weathering on one hand, and seawater intrusion and anthropogenic contamination on the other. A plot of the factor scores for the two major sources of variation in the salinity revealed trends which can be used in hydrogeological mapping and assist in drilling potable water boreholes in southeastern Ghana. This study also revealed four major spatial groundwater groups: low salinity, acidic groundwaters which are mainly derived from the Birimian and Togo Series aquifers; low salinity, moderate to neutral pH groundwaters which draw membership mainly from samples of the Voltaian, Buem and Cape Coast granitoids; very high salinity waters which are not suitable for most domestic and irrigation purposes and are mainly from the Keta Basin aquifers; and intermediate salinity groundwaters consisting of groundwater from the Keta basin aquifers with minor contributions from the other major terrains. The major water type identified in this study is the Ca–Mg–HCO₃ type, which degrades into predominantly Na–Cl–SO₄ more saline groundwaters towards the coast.     

Hydrogeochemical characterization and quality assessment of groundwater using self-organizing maps in the Hangjinqi gasfield area,Ordos Basin,NW China

Water resources are scarce in arid or semiarid areas,which not only limits economic development,but also threatens the survival of mankind.The local communities around the Hangjinqi gasfield depend on groundwater sources for water supply.A clear understanding of the groundwater hydrogeochemical characteristics and the groundwater quality and its seasonal cycle is invaluable and indispensable for groundwater protection and management.In this study,self-organizing maps were used in combination with the quantization and topographic errors and K-means clustering method to investigate groundwater chemistry datasets.The Piper and Gibbs diagrams and saturation index were systematically applied to investigate the hydrogeochemical characteristics of groundwater from both rainy and dry seasons.Further,the entropy-weighted theory was used to characterize groundwater quality and assess its seasonal variability and suitability for drinking purposes.Our hydrochemical groundwater dataset,consisting of 10 parameters measured during both dry and rainy seasons,was classified into 6 clusters,and the Piper diagram revealed three hydrochemical facies:Cl-Na type(clusters 1,2 and 3),mixed type(clusters 4 and 5),and HCO3-Ca type(cluster 6).The Gibbs diagram and saturation index suggested thatweathering of rock-forming mineralswere the primary process controlling groundwater chemical composition and validated the credibility and practicality of the clustering results.Two-thirds of 45 groundwater samples were categorized as excellent-or good-quality and were suitable as drinking water.Cluster changes within the same and different clusters from the dry season to the rainy season were detected in approximately 78%of the collected samples.The main factors affecting the groundwater quality were hydrogeochemical characteristics,and dry season groundwater quality was better than rainy season groundwater quality.Based on this work,such results can be used to investigate the seasonal variation of hydrogeochemical characteristics and assess water quality accurately in the others similar area.