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.     

Use of multivariate statistical methods in data-base maintenance

Multivariate statistical methods may be used to enhance large data bases by predicting missing information and verifying unchecked data vectors. In addition, new techniques may be used for exploratory purposes to investigate the interrelationships between variables. The techniques are being applied successfully in coal mining.     

Stratigraphic Division and Correlation of the Nihewan Beds by Multivariate Statistical Analysis

Described in paper is the principle of optimal partitioning method for stratigraphic division and correlation.The Nihewan Beds are taken for example to show how to apply this approach in stratigraphic division and correlation.The semiquantitative spectral analysis data on aggregate trace elements in 324 samples taken from the nine sections in the Nihewan Basin are treated with multivariate statistical method for stratigraphic division and correlation.First ,the data from all the sections are respectively calculated by the optimal partitioning method to establish the stratigraphic boundaries.The optimal partitioning method has proved itself to be applicable to stratigraphic division and correlation. In our practice the Nihewan Beds are divided into five zones (I-V).Zone I includes subzones Ia and Ib,Zones Ia,Ib,II and III are considered to be corresponding to the Pliocene(N2),the early Early Pleistocene,the late Early Pleistocene,and the Middle Pleistocene,respectively .Zones IV and V are probably Late Pleistocene in age.This indicated that sediments deposited con-temporaneous in the sections of the same basin are similar in geochemical characteristics,although dif-ferent in geographical location.However,the sediments also show some variations ,with a transitional relationship from one section to another .For example ,in Zone II,the sediments of the Xiaodukou section show not only the characteristics of the Nangou-Hongya and Hutouliang sections,but also those of the Xiashagou,Shixiaxi,Shixiadong and Wulitai sections.It can be seen from the above that the zones can be characteristically correlated with one another.In addition the feasibility of the optimal partitioning method is also described in the present paper.     

Climatic classification of the Tibet Autonomous Region using multivariate statistical methods

A climatic regionalization of the Tibet (Xizang) Autonomous Region (TAR) is developed based on a multivariate analysis of temperature and precipitation records of two data sets from the periods 1971–1980 and 1980–1989. For these two decades 15 selected variables of the 29 meteorological stations — in total more than 50,000, partly handwritten original data — were computed. Three different statistical approaches, Cluster Analysis (CA), Factor Analysis (FA) and Discriminant Analysis (DA) were followed up. The vast expanse (1.2 million km²) and the pronounced relief of the TAR (between 500 m and 8,848 m in elevation), the low density and unequal distribution of meteorological stations, as well as uncertainties inherent in the selection of statistical methods, restricted and hampered the separation of coherent climatic subregions using multivariate statistics. However, a solution comprising of nine clusters, representing the different climatic conditions of Tibet, was found.The results of the multivariate statistical analyses were compared with traditional classification schemes published by the Chinese Academy of Sciences (CAS). The Chinese classifications from the years 1982 (CAS 82) and 1984 (CAS 84) are here presented to the scientific community of the western countries for the first time (Fig 2 and 3). The main aim of these Chinese climatic classifications in Tibet was the delineation of areas with the best climatic conditions for agricultural land-use. In comparison, the aim of this paper was to establish a new classification of Tibet's climate, mainly based on measurements of climatic elements analyzed with multivariate statistical procedures following up the approach of McGregor (1993). The Factor Analysis (FA) included the temperature factor, which explains 46% of the total variance, whereas 32% is explained by the winter moisture and 12% by the moisture factor.For temperatur zonation and, in particular, for the distribution of precipitation, the high mountain topography of Tibet is interpreted as the determining factor. The new climatic classification derived from multivariate statistics allows a more dynamic interpretation of the climatic cluster pattern. First, it shows the channelized influence of the summer monsoon along the southeast-northwest- and east-west-trending broad valleys north of the Gulf of Bengal. This is also obvious in the pattern of the temperature and moisture factors. Second, it can be supposed that a general south-trending influence of the winter monsoon, in combination with a northwest-trending influence from the Bay of Bengal leads to more irregular relief- and wind-dependent pattern, which can be estimated from the distribution of the winter moisture factor.     

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.     

基于多元统计和傅立叶和谱分析的土壤重金属的来源解析及其风险评价

分析珠江三角洲腹地佛山顺德区208个蔬菜地表层土样Cu、Ni、Cr、As、Pb、Zn、Cd和Hg等8种重金属的全量,结果表明,8种重金属的平均浓度高于广东省土壤背景值。Cd和Hg的最高浓度和变异系数分别为6.54mg/kg、115%和4.82mg/kg、151%,暗示Cd和Hg的人为来源。多元统计与傅立叶和谱分析的结合,解释了Cr、Ni和Cu的自然来源,Pb、Zn、As、Cd和Hg的人为来源;傅立叶和谱分析进一步阐释了Zn与Cu的双重来源,并推断土壤Hg来源于大气沉降。研究区内大约21.7%的土壤受重金属污染,表明需要调整该区的农业生产活动。     

Correlation analysis of statistical facies fault models

Doklady Earth Sciences - This paper addresses seismic imaging of fault zones and analysis of the seismic data with the use of the fault facies model developed at Uni Research CIPR. Simulated and...     

The use of multivariate statistical analysis in the assessment of groundwater hydrochemistry in some parts of southwestern Nigeria

Arabian Journal of Geosciences - Turabah area is located in the southwestern Arabian Shield of Saudi Arabia. The present study aims to shed light on the origin and mechanism of formation of the...     

The Finne fault zone (central Germany): structural analysis of a partially inverted extensional fault zone by balanced cross-sections

The Finne fault zone, located in central Germany to the southwest of the Harz mountains, was studied by means of detailed map analysis, investigations of fault displacement and balanced cross-sections for the most strongly deformed area in the center of the fault zone (ca. 50?% of total fault zone length). The system of the Finne fault zone shows a nearly 100-km-long straight flexure that symbolizes the morphological and geological northeastern border of the Thuringian basin. In the central part, which should be surveyed here, the fault zone corresponds to a distinctive narrow band of highly deformed Triassic sedimentary rocks. The northwestern and especially the southeastern parts of the research area are developed as several parallel branch faults. In the southeastern elongation of the fault zone, which is not part of our survey, the sedimentary cover is missing. Here, it is possible to gain insight to the fact that the basement is also involved to the kinematics of the fault zone. Based on our results, we propose a subdivision of the fault zone into four sectors. From the northwest to the southeast, we interpret the structure of these sectors to reflect (1) a compressional flexure, (2) an overthrust graben, and (3) a partially inverted and folded half graben. In the extreme southeast (4), the fault zone is characterized by an anticline with some strike-slip movement parallel to the fold axis. This segmentation is caused by a thrust fault system whose strike direction deviates slightly from that of the earlier formed graben system. The structural configuration can be explained by a two-phase deformation, in which the contractional strain exceeded the preceding extensional deformation. In the investigated area, the horizontal shortening attains a maximum of ca. 1?km. The present study confirms many earlier hypotheses, presents new results on the deformation history of the fault zone, and attempts to evaluate the deformation in a regional geological context. The results of earlier studies were refined and revised using modern methods, and a unified structural and kinematic model of the Finne fault zone was created.     

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 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.     

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.     

多元统计分析在普朗斑岩型铜矿床中的应用

普朗斑岩型铜矿是云南格咱岛弧成矿带中印支期斑岩型铜矿床的典型代表。本文应用聚类分析、因子分析方法对普朗斑岩型铜矿成矿岩体中微量元素进行了分析和科学分类。根据普朗复式斑(玢)岩体的地质条件和微量元素地球化学特征,从理论角度定性分析和定量分析均确定了普朗复式岩体存在明显的Cu-Au-Ag矿化异常,主成矿元素Cu与Au、Ag、Mo、W等具有较好的相关性,且局部存在中―低温的Pb、Zn矿化异常组合。矿床的形成与印支期中酸性斑(玢)岩体的侵入有密切的联系,成矿作用具多期多阶段性。     

Water and sediment quality assessment in the mid-Black Sea coast of Turkey using multivariate statistical techniques

The aim of this study was to investigate the water and sediment quality in the mid-Black Sea coast of Turkey. The samples were collected from six stations during 2007. Investigated parameters were total carbon (TC), total inorganic carbon (TIC), total organic carbon (TOC), ammonium-nitrogen (NH₄-N), nitrate-nitrogen (NO₃-N), nitrite-nitrogen (NO₂-N), total phosphorus (TP), sulphate, total hardness, methylene blue active substances (MBAS), phenol, adsorbable organic halogens (AOX), dissolved oxygen (DO), pH and electrical conductivity (EC) in water samples and TC, TIC, TOC, TP, pH, electrical conductivity (EC), redox potential (Eh) and water content (WC) in sediment samples. Different multivariate statistical techniques were used to evaluate variations in surface water and sediment quality. Principal component analysis helped in identifying the factors or sources responsible for water and sediment quality variations. Five factors were found responsible for 87.63% of the total variance in the surface waters. In sediments, three factors explained 84.73% of the observed total variance. Cluster analysis classified the monitoring sites into two groups based on similarities of water and sediment quality characteristics.     

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.     

Assessment of seasonal variations of chemical characteristics in surface water using multivariate statistical methods

Water pollution has become a growing threat to human society and natural ecosystems in the recent decades. Assessment of seasonal changes in water quality is important for evaluating temporal variations of river pollution. In this study, seasonal variations of chemical characteristics of surface water for the Chehelchay watershed in northeast of Iran was investigated. Various multivariate statistical techniques, including multivariate analysis of variance, discriminant analysis, principal component analysis and factor analysis were applied to analyze river water quality data set containing 12 parameters recorded during 13 years within 1995–2008. The results showed that river water quality has significant seasonal changes. Discriminant analysis identified most important parameters contributing to seasonal variations of river water quality. The analysis rendered a dramatic data reduction using only five parameters: electrical conductivity, chloride, bicarbonate, sulfate and hardness, which correctly assigned 70.2 % of the observations to their respective seasonal groups. Principal component analysis / factor analysis assisted to recognize the factors or origins responsible for seasonal water quality variations. It was determined that in each season more than 80 % of the total variance is explained by three latent factors standing for salinity, weathering-related processes and alkalinity, respectively. Generally, the analysis of water quality data revealed that the Chehelchay River water chemistry is strongly affected by rock water interaction, hydrologic processes and anthropogenic activities. This study demonstrates the usefulness of multivariate statistical approaches for analysis and interpretation of water quality data, identification of pollution sources and understanding of temporal variations in water quality for effective river water quality management.     

Application of multivariate statistical techniques in the assessment of water quality in Sakarya River,Turkey

In this paper, the surface water quality of the Sakarya River in Turkey is assessed by using multivariate statistical techniques. These techniques were applied to the chemical parameters obtained from the five different surface water quality observation stations. Factor and principal component analysis results reveal that the agricultural, anthropogenic and domestic pollution caused differences in terms of water quality. Cluster analysis revealed two different clusters of similarities between the stations, reflecting different chemical properties and pollution levels in the studied river. Surface water quality downstream of the river was different from the water quality upstream. Thus, this study shows the usefulness of multivariate statistical techniques for analysis and interpretation in the surface water quality problem.     

断层破裂带附近采场采动效应的流固耦合分析

矿井底板突水是一个复杂的多物理场耦合问题,结合含断层破裂带条件下采场开采的工程背景,通过离散元流固耦合分析,研究了采场工作面推进过程中断层带的变形与受力情况以及底板支承压力、渗流矢量和渗流速度的动态发展规律和分布特征。相关模拟结果表明,采场中煤层的开采与断层破裂带之间是相互影响的,以支承压力为代表的采动应力是底板破坏形成导水裂隙带及断层“活化”突水的一个主要诱因,而断层的存在也使得工作面与断层带范围内的围岩应力更加集中,增大了底板破坏突水的危险性。采动过程中,底板破坏所形成的导水裂隙带主要集中在工作面前方及下方围岩中,这些区域渗流速度较大,是形成突水的主要通道。