In geochemical applications, data classification commonly involves 'mapping' continuous variables into discrete descriptive categories, and often is achieved using thresholds to define specific ranges of data as separate groups which then can be compared with other categorical variables. This study compares several classification methods used in applied geochemistry to select thresholds and discriminate between populations or to recognize anomalous observations. The comparisons were made using monte carlo simulation to evaluate how well different techniques perform using different data set structures. A comparison of maximum likelihood parameter estimates of a mixture of normal distributions using class interval frequencies versus raw data was undertaken to study the quality of the corresponding results. The more time consuming raw data approach produces optimal parameter estimates while the more rapid class interval approach is the approach in common use. Results show that provided there are greater than 50 observations per distribution and (on average) 10 observations per class interval, the maximum likelihood parameter estimates by the two methods are practically indistinguishable. Univariate classification techniques evaluated in this study include the 'mean plus 2 standard deviations', the '95th percentile', the gap statistic and probability plots. Results show that the 'mean plus 2 standard deviations' and '95th percentile' approaches are inappropriate for most geochemical data sets. The probability plot technique classifies mixtures of normal distributions better than the gap statistic; however, the gap statistic may be used as a discordancy test to reveal the presence of outliers. Multivariate classification using the background characterization approach was simulated using several different functions to describe the variation in the background distribution. Comparisons of principal components, ordinary least squares regression and reduced major axis regression indicate that reduced major axis regression and principal components are not only consistent with assumptions about geochemical data, but are less sensitive to varying degrees of data set truncation than is ordinary least squares regression. Furthermore, correcting the descriptive statistics of a truncated data set and calculating the background functions using these statistics produces residuals and scores which are predictable and thus can be distinguished easily from residuals and scores calculated for data from another distribution. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

A broad-based geochemical approach, including chemical and isotopic analyses of ground water, chemical analysis of aquifer materials, and laboratory water-rock experiments, was used to evaluate the origin and chemical evolution of ground water on La Palma, a volcanic island in the Canary Archipelago. Stable isotopes of oxygen, hydrogen, carbon and sulfur were successfully used to delineate recharge zones and identify solute sources. Laboratory study of water-rock interactions established the source of solutes and the nature of the chemical reactions that control ground-water chemistry. Most ground water on La Palma originates in a recharge zone that encircles the island from 500 to 1800 meters above sea level. Dry fallout and seaspray are minor sources of solutes, however, evaporative concentration during recharge may produce elevated chloride levels in some portions of the island. Laboratory water-rock experiments and ground-water analyses indicate that incongruent dissolution of aluminosilicate minerals is the dominant process of solute acquisition. The geochemical evolution of most waters is controlled by the availability of dissolved carbon dioxide gas. However, oxidation of pyrite enhances the reactivity of ground water in some portions of the island. Waters in the early phases of chemical evolution appear to be in equilibrium with a kaolinite alteration product, whereas more mineralized waters have compositions consistent with smectite equilibrium. Zones or compartments of ground-water flow were delineated by classifying sampling sites into geochemically distinct groups. Eight distinct zones of ground-water flow were identified using these criteria, including superimposed but hydrologically separate flow paths.