Sedimentary facies of barataria bay,Louisiana determined by multivariate statistical techniques

A multivariate statistical strategy employing cluster analysis, discriminant analysis, and ordination was used to classify and interpret depositional environments of Barataria Bay, Louisiana, from grain-size data tabulated by Krumbein and Aberdeen (1937). Weight-percent whole-phi variables for 69 samples were tested for redundancy using R-mode cluster analysis. These samples were partitioned into five environmentally significant facies using Q-mode cluster analysis: (1) beach-ridge sand; (2) shallow wave-zone sand; (3) channel sand and silty sand; (4) channel-margin silty sand; and (5) low-energy sandy silt and clayey silt. Then the classification was extended with discriminant analysis to the remaining 29 samples which exhibited incipient flocculation and whose constituents did not total unity. Environments of deposition were associated with each facies following the method of Visher (1969) and using gradient analysis on a two-dimensional Q-mode ordination. Wilk's lambda and discriminant analysis tested the statistical significance of these facies; they were further tested by comparing their distribution with field relations and known environmental processes.     

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.     

A multivariate sedimentary environmental analysis of Great South Bay and South Oyster Bay, New York

A multivariate statistical strategy for classifying paleoenvironments is effective for studying modern sedimentary processes in western Great South Bay and South Oyster Bay, New York. The 13 whole phi weight percent variables were tested for redundancy with R-mode cluster analysis. The samples were partitioned statistically into five environmentally significant facies using Q-mode cluster analysis: (A)sandy gravel, (B)sandy silt, (C)silty sand, (D)slightly gravelly sand, and (E)fine sand. An ordination depicted gradational relationships among the samples and the facies. It was used to evaluate the environmental and textural parameter gradients within the sample space. Interpretations obtained in this manner and by examination of the grain-size curves suggest that these sediments were deposited by waves and currents on beaches and in wave zones (facies C and E),shoal areas (facies B),and tidal channels (facies A and D).Tidal currents, wave action, and eelgrass control the distribution of sediments within the two bays.     

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.     

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.     

Comparison of automatic classification methods applied to lake geochemical samples

Geochemical samples from part of Lake Geneva were analyzed for 29oxides and trace elements. The variables and samples were subjected to R- and Q-mode analyses. The following techniques were applied in sequence: data transformation (normalization and standardization), data reduction (principal component and factor analysis), and automatic classification (dendrograph). The data were treated using various combinations of these techniques, and the resulting classifications evaluated by means of several criteria. The best classification of the samples is given by a cluster analysis performed on four principal components computed from standardized variables. The discriminatory power of the variables also was measured and determined to depend on their degree of intercorrelation. As a final result, the 29original variables were reduced to four components and the sediment samples classified into four facies, leading to easily interpretable geochemical maps.     

Numerical analysis as applied to the environmental interpretation of carbonate microfacies of some sub-Himalayan carbonates (lower upper precambrian) in northwestern India

Forty-three samples of (1) Sirban Limestone of Riasi, Jammu and Kashmir State, India, based on six mineralogic and petrographic presence-absence variables, and (2) 36 samples of Bilaspur Limestone based on 11 presence-absence mineralogic and petrographic variables, were numerically classified by Q-mode cluster analysis using Sokal and Michner's Simple Matching Coefficient. Sirban Limestone of Riasi yielded 10 clusters or groups indicating four depositional environments: (1) intertidal, (2) intertidal to subtidal, (3) subtidal, and (4) deep-water basinal. Similarly, Bilaspur Limestone yielded nine clusters indicative of the same four environments. A Q-mode ordination of the Riasi samples and of Bilaspur Limestone shows a generalized shelf-to-basin carbonate deposition profile. Results of this study substantiate earlier conclusions of Rao (1979) based on field, mineralogic, and petrographic study of the above-mentioned carbonates.     

Differentiating fluvio-marine depositional environments in the Nile Delta using textural and compositional components

Textural and coarse fraction compositional components are evaluated to distinguish samples from modern environments of the Nile Delta of Egypt. These environments include: river, coastal dune, accretion ridges, beach, neashore, lagoon and prodelta. In this study petrological variables (12 textural and 18 mineralogical, faunal and floral) were considered for each sample. Discrimination was achieved by using simple bar graphs of the raw data for each environment and Q-mode factor analysis. The factor analysis yielded four compositional assemblages: Factor 1 is dominated by terrigenous fine sand; factor 2 consists of biogenic mud; factor 3 contains terrigenous coarse and medium sands; and factor 4 comprises composite silty sand. Discrimination of the seven environments is generally good, with a lower resolution for beach, coastal dune and river sands.Having discriminating the examined environments using Q-mode factor analysis, a graphic model was constructed to help determine the origin of ‘unknown’ samples. As a test, this model is satisfactory in identifying and interpreting the origin of sediments of Holocene age from two additional cores recovered off the delta coast.     

Hydrogeochemistry and geothermometry of thermal springs from the Guelma region,Algeria

This paper reports the results of our studies, the chemical analysis of thermal spring’s waters and their geological settings, the use of different statistical methods to evaluate the origin of the dissolved constituents of spring waters and the estimation of the reservoir temperature of the associated geothermal fields of the Guelma region, Algeria. A major component in 13 spring water samples was analyzed using various techniques. The waters of the thermal springs at Guelma basin vary in temperature between 20 and 94oC. Q-mode hierarchical cluster analysis suggests three groups. The water springs were classified as low, moderate and high salinity. Mineral saturation indices (SI) calculated from major ions indicate the spring waters are supersaturated with the most of the carbonate minerals, and all of the spring water samples are under-saturated with evaporite minerals. The thermal spring waters have a meteoric origin, and all samples are immature with strong mixing between warm and shallow waters, where the temperatures of reservoirs to which the thermal waters are related ranged between 64° and 124°C. The deep circulation of meteoric waters in the study area is supplied by the high geothermal gradient around 4.5°C per 100 m and reaches a high temperature before rising to the surface. The estimated circulation depths ranged from 1425 and 3542 m.     

Evaluation of graphical and multivariate statistical methods for classification of water chemistry data

A robust classification scheme for partitioning water chemistry samples into homogeneous groups is an important tool for the characterization of hydrologic systems. In this paper we test the performance of the many available graphical and statistical methodologies used to classify water samples including: Collins bar diagram, pie diagram, Stiff pattern diagram, Schoeller plot, Piper diagram, Q-mode hierarchical cluster analysis, K-means clustering, principal components analysis, and fuzzy k-means clustering. All the methods are discussed and compared as to their ability to cluster, ease of use, and ease of interpretation. In addition, several issues related to data preparation, database editing, data-gap filling, data screening, and data quality assurance are discussed and a database construction methodology is presented. The use of graphical techniques proved to have limitations compared with the multivariate methods for large data sets. Principal components analysis is useful for data reduction and to assess the continuity/overlap of clusters or clustering/similarities in the data. The most efficient grouping was achieved by statistical clustering techniques. However, these techniques do not provide information on the chemistry of the statistical groups. The combination of graphical and statistical techniques provides a consistent and objective means to classify large numbers of samples while retaining the ease of classic graphical presentations. Electronic Publication     

Comparison of interpretations of geochemical soil data by some multivariate statistical methods, Key Anacon, N.B., Canada

The nature of the information - and its usefulness - that can be obtained from some of the more common multivariate statistical techniques is illustrated by their application to H and B horizon soils analyzed for 16 variables from the vicinity of the Key Anacon massive sulphide deposit (New Brunswick, Canada) where the geochemical response is erratic and the contrasts low. The theoretical bases of the statistical techniques are given in an appendix.Stepwise linear discriminant functions are employed as a classifying technique on H horizon soils to identify a regional anomaly, and on B horizon soils to derive discriminant scores to define the location of the sulphide zone. R-mode nonlinear mapping (RNLM) indicates that the variables Hg, Cl⁻, and conductance are closely correlated with the organic carbon content; variations in the latter are clearly related to variations in the secondary environment.Q-mode NLM using Pb, Zn, Co, and Ni as variables (identified as good discriminators by stepwise linear discriminant function) identify “outlying” anomalous samples related to the mineralized zones. A principal component biplot (using the same variables employed in the Q-mode NLM) indicates essentially the same samples as being anomalous as the Q-mode NLM. The biplot technique has the added advantage of also indicating which variable(s) is responsible for any particular sample being identified as anomalous.The practical result of the investigation is that the zone of sulphide mineralization defined by drilling and from underground data is confidently identified and defined. A number of geophysical magnetic anomalies over the same stratigraphic horizon has a relatively weak or no geochemical response, although a few locations are defined as second priority targets for follow-up work.     

Hydrochemical classification and multivariate statistical analysis of groundwater from Wadi Sahba area in central Saudi Arabia

The central region of Saudi Arabia is underlain by thick sedimentary formations belonging to the Mesozoic and Cenozoic era. These sedimentary formations form a prolific aquifer supplying groundwater for agricultural and domestic usage in and around Riyadh. The region south of Riyadh City is well known for agricultural activities. Wadi Sahba, which is an eastward extension of Wadi Nisah, has readily available groundwater resources in the Cretaceous Biyadh sandstone aquifer to sustain agricultural activities. The objective of the present study was the hydrochemical assessment of groundwater in the area to understand the main hydrological processes which influence groundwater chemistry. To achieve this objective, 20 groundwater samples were collected from agricultural farms in the Wadi Sahba in central Saudi Arabia, and the major physiochemical constituents were analyzed and interpreted. The average TDS value of the analyzed samples is 1578.05 mg/l, whereas the average EC concentration is 3220.05 μS/cm. Groundwater facies classification inferred from the Piper plot shows that groundwater in the study area belongs to the Ca-SO₄-Cl type and Ca-Na-SO₄-Cl type. The Ca-SO₄-Cl type of groundwater facies is influenced mainly by gypsum dissolution and base ion exchange, whereas the Ca-Na-SO₄-Cl type is influenced by gypsum and halite dissolution. All the groundwater samples are undersaturated with respect to these two principal mineral phases. The Q-mode cluster analysis results in two main groups of groundwater samples, mainly based on the TDS content. Cluster 1 has an average TDS value of 1980 mg/l, whereas cluster 2 has an average TDS of 1176 mg/l. The groundwater facies identified through the Piper plot reflects the major hydrological processes controlling groundwater chemistry in the area and was found to be more useful in this study as compared to cluster analysis.     

Significance of Detrended Correspondence Analysis (DCA) in palaeoecology and biostratigraphy: A case study from the Upper Cretaceous of Egypt

The Cenomanian–Turonian macrofauna from the Sinai Peninsula, Egypt offers an excellent opportunity to test the applicability of gradient analysis in palaeoecology and biostratigraphy. Detrended Correspondence Analysis (DCA) is a simple multivariate technique for arranging species and samples along environmental gradients. In order to reconstruct palaeoecological patterns and biostratigraphy, 42 samples, 4564 individuals, and 132 species from three sections of eastern Sinai were subjected to DCA. Compared with other multivariate techniques such as cluster analysis, the macrobenthic associations (obtained by DCA) fall fully within or deviate only slightly from associations obtained by cluster analysis. However, DCA makes it possible to arrange these associations from completely random distribution (as tested by cluster analysis) to a temporal gradient. Therefore, it is possible to use this multivariate technique also as a useful tool in biostratigraphy. The first detrended correspondence axis (DC1) reflects a water-depth gradient from onshore to offshore, higher scores being typical of onshore samples from the southernmost section and lower scores being typical of offshore samples from the northern section. Overprinted on the DC1 axis is also a gradient of life and feeding modes, as samples with low scores are dominated by epifaunal species and samples with high scores display a higher proportion of shallow-infaunal taxa. With respect to the second detrended correspondence axis (DC2), substrate composition and water energy are overprinted on this axis as samples with low scores predominantly are coarse-grained carbonates (e.g., reefal rudstone), while samples with high scores primarily are mixed-siliciclastics/carbonates (e.g., marl), which are dominated by low-energy taxa. Because the substrate conditions are closely related to the water energy, the coarse-grained substrates were deposited under high water energy, while the marly facies was deposited under low-energy conditions. Excursions in DC2 scores, reflecting substrate composition and water energy, are used to reconstruct the macrobenthic associations; eight associations and two assemblages were recognized. High stress environments (low DC2 scores) were occupied by less diverse associations such as the Chondrodonta joannae association and the Pchelinsevia coquandiana–Praeradiolites biskraensis association. The latter association is stratigraphically followed by high-diversity associations such as the Ilymatogyra africana–Rhynchostreon suborbiculatum association, which preferred less-stressed environments (high DC2 scores).     

Vector analysis of chemical variation in the lavas of Parícutin volcano,Mexico

Compositional variations in the lavas of Parícutin volcano, Mexico, have been examined by an extended method of Q-mode factor analysis. Each sample composition is treated as a vector projected from an original eight-dimensional space into a vector system of three dimensions. The compositions represented by the vectors after projection are closely similar to the original compositions except for Na₂Oand Fe₂O₃.The vectors in the three-dimensional system cluster about three different planes that represent three stages of compositional change in the Parícutin lavas. Because chemical data on the compositions of the minerals in the lavas are presently lacking, interpretations of the mineral phases that may have been involved in fractional crystallization are based on CIPW norm calculations. Changes during the first stage are attributed largely to the fractional crystallization of plagioclase and olivine. Changes during the second stage can be explained by the separation of plagioclase and pyroxene. Changes during the final stage may have resulted mostly from the assimilation of a granitic material, as previously proposed by R. E. Wilcox.     

Investigation of hydrochemical characteristics of groundwater from the Cretaceous-Eocene limestone aquifer in southern Ghana and southern Togo using hierarchical cluster analysis

The most relevant controls on the water quality within the Cretaceous-Eocene limestone aquifer of the Keta Basin, Ghana, and the coastal sedimentary basin of Togo were assessed using Q-mode hierarchical cluster analysis (HCA) and mass-balance modelling. The pattern recognition technique of HCA was employed for partitioning hydrochemical data from a total of 65 surface and borehole samples from the study area into water groups. A spatial plot of the water groups consisting of samples from the limestone aquifer shows that the vast majority of samples belonging to the same group are located in close proximity to one another, suggesting the same processes and/or flow paths in the limestone aquifer system. Geochemical reaction models of selected water groups were constructed using PHREEQC-2. The hydrochemical compositions of the water groups and the mass-balance calculations indicate that the dominant processes and reactions responsible for the hydrochemical evolution in the system are: (1) carbonate equilibria, (2) silicate weathering reactions, (3) limited mixing with saline water, and (4) ion exchange. The combined use of HCA and mass-balance modelling has shown to be a useful approach in interpreting groundwater hydrochemistry in an area where large uncertainties exist in the understanding of the groundwater flow system.     

Condensing multi-element reconnaissance geochemical data from south Greenland using empirical discriminant analysis

Empirical discriminant analysis classified multivariate data from 2174 geochemical reconnaissance samples from South Greenland, so that they were related to known geological units or characterized as outliers. Training sets, comprising 514 samples from 14 geologic units were selected in order to reflect only the background conditions of each geological unit. A smoothing parameter of 0.5 maximized correct classification of the training sets and extracted a reasonable number of outliers (289, 13% of the samples) representing geographically grouped anomalies. Plots of the geochemical samples classified into the geological units corresponded well to the geological map.Q-mode cluster analysis classified the 289 outliers into 30 groups with different element associations. All types of mineral occurrence known in South Greenland could be recognized amongst the clusters. For example, there were seven clusters which were characterized by samples with high U values and different associated elements each one related to a different type of U mineralization. Another cluster containing samples with high Zr, Nb, and Y values reflects recently discovered pyrochlore mineralization. Other clusters were explained on the basis of geological units which were too small to be mapped or included amongst the training sets.Empirical discriminant analysis successfully reduced the multivariate data to one map, which made it easier to evaluate the varying element levels over the different geological units. Incorrectly classified samples require follow-up in order to appraise the accuracy of the geological mapping. Classification of the outliers by cluster analysis assists both in identifying samples influenced by mineral occurrences and in predicting the type of mineralization to be expected, thereby substantially aiding in the selection of areas for mineral exploration.     

黄骅坳陷新近系馆陶组重矿物特征及物源区意义

黄骅坳陷馆陶组发育一套以辫状河沉积为主的沉积体系,储集物性较好,是研究区内的重要储油层。整个黄骅坳陷新近系物源研究还处于空白状态。本文重点利用统计学中的Q型聚类及R型聚类的方法对重矿物含量特征进行分析,划分出不同的重矿物组合区及相应的母岩类型。研究结果表明:根据重矿物含量特征可划分出A—D 4个不同的重矿物组合区,其中A、B、C区的母岩类型与周围燕山、沧县、埕宁3个古隆起的岩石类型能很好对应,重矿物稳定系数所揭示的物源方向也与3个古隆起位置相吻合;D区与前3个分异性很大,且重矿物稳定系数极高,应为远源搬运的沉积物,远于周围的古隆起,可能与古黄河沉积物有关。     

A GIS-based approach for detecting pollution sources and bioavailability of metals in coastal and marine sediments of Chabahar Bay,SE Iran

Chabahar Bay in SE of Iran is a shallow semi-enclosed environment affected by anthropogenic activities. In this paper, 19 sediment samples were collected and concentration of selected metals (Cu, Pb, Zn, Cd, Ni, Cr, Co, V and Fe) was determined using ICP-MS analytical method. Sediment samples from five stations were also selected for sequential extraction analysis and concentration of metals in each fraction was determined using ICP-OES. In order to investigate the environmental quality of Chabahar Bay, geographic information system (GIS) along with geochemical data, environmental indices and statistical analyses were used. Calculated contamination degree (C_d) revealed that most contaminated stations (Ch3, S1 and S3) are located SE of Chabahar Bay and contamination decreases in a NW direction. The S9 station, west of the bay, is also contaminated. High organic matter (OM) content in the sediments is most likely the result of fuel and sewage discharge from fishing vessels along with discharge of fishing leftovers. Significant correlation coefficient among OM, Fe, Cu, Pb, Zn and Cd seemingly reflects the importance of the role that OM and Fe oxy-hydroxides play in the metals mobility. The results of hierarchical cluster analysis (HCA), computed correlation coefficient and sequential extraction analysis suggest that Cu, Pb, Zn and Cd probably come from antifouling and sea vessel paints, while Ni, Cr, Co, V and Fe are most likely contributed by ophiolitic formations located north of the bay and/or deep sea sediments. Average individual contamination factors (ICFs) indicated that the highest health hazard from the bay is posed by Cu, Pb and Zn.     

Semi-hierarchical correspondence cluster analysis and regional geochemical pattern recognition

Semi-hierarchical correspondence cluster analysis (SHCCA), firstly developed in this paper, extracts the main advantages of correspondence analysis, hierarchical and non-hierarchical cluster analysis, and unifies the R- and Q-mode cluster analysis of large data set. A systemic program to recognize the regional geochemical patterns is built up based on this method. With this program, the complex tasks for data interpretation can be achieved by simple processes, and important geochemical information can be displayed by a single diagram, i.e. the multivariate regional geochemical image. As one of the applied examples of this program, the regional geochemical pattern recognition for a shallow covered area around Tahe in Heilongjiang Province is introduced. The results show that many hidden geochemical patterns related to the lithologies, structures, ore-forming conditions and prospecting targets etc are revealed by the geochemical image, and that the main geochemical patterns are related with certain geological and gravitational patterns. By finding contrasts between geochemical patterns and geological or gravitational patterns, the SHCCA results assist the geological mapping in this area. Geochemical data obtained in Chinese regional geochemical exploration provides useful information regarding geology and minerals, and the method described in this paper provides a new way to examine this type of resource.     

Analysis of groundwater quality using water quality index and conventional graphical methods: the Volta region,Ghana

Conventional graphical and statistical methods were used with water quality indices to characterize the hydrochemistry of groundwater from the northern part of the Volta region of Ghana. The objective was to determine the processes that affect the hydrochemistry and the variation of these processes in space among the three main geological terrains: the Buem formation, Voltaian System and the Togo series that underlie the area, and to determine the suitability of groundwater from the area for drinking purposes. The Q-mode cluster analysis reveals three main water groups. The groups established from the Q-mode HCA appear to indicate different degrees of weathering which could further indicate varying levels of fracturing aquifer hydraulic properties. R-mode HCA and factor analysis (using varimax rotation and Kaiser Criterion) were then applied to determine the significant sources of variation in the hydrochemistry. This study finds that groundwater hydrochemistry in the area is controlled by the weathering of silicate and carbonate minerals, as well as the chemistry of infiltrating precipitation. Mineral activity diagrams for the CaO–Na₂O–Al₂O₃–SiO₂–H₂O and CaO–MgO–Al₂O₃–SiO₂–H₂O systems plotted for the area indicate stability in the smectite field and attribute hydrochemistry to the weathering of silicate minerals. Silicate mineral weathering and the effects of precipitation appear to be pervasive among all the three main geological terrains, whereas carbonate weathering is localized among the Voltaian aquifers. Cation exchange does not appear to play a significant role in the hydrochemistry but mild Water quality indices (WQI) were calculated for the samples using the concentrations of Na⁺, Ca²⁺, Mg²⁺, Cl⁻, NO₃ ⁻, F⁻, and EC at the various sample locations. The WQI values indicate that groundwater from the study area is of excellent quality for drinking purposes. WQI values from groundwater samples are averagely higher than samples taken from surface water sources in the area. This implies that geology has had an impact on the WQI of groundwater in the area.