An evaluation of regional stream sediment data by advanced statistical procedures
Creators: name: Matysek, Paul Frank
Publisher: name: University of British Columbia
Year: 2010

description: This study was directed towards the development of rigorous, systematic, computer-assisted statistical procedures for the interpretation of quantitative and qualitative data commonly encountered in practical exploration-oriented surveys. A suite of data analysis tools were developed to evaluate the quality of geochemical data sets, to investigate the value and utilization of categorical field data, and to recognize and rank anomalous samples. Data obtained from regional stream sediment surveys as undertaken by the British Columbia Ministry of Energy, Mines and Petroleum Resources in southern British Columbia were examined as a case history. A procedure based on a statistical analysis of field-site duplicates was developed to evaluate the quality of regional geochemical silt data. The technique determines: (1) whether differences in metal concentrations between sample sites reflect a real trend related to geological and geochemical features and not merely a consequence of sampling and analytical error, and (2) absolute precision estimates at any particular accumulation across a metal's concentration range. Results for metals Zn, Cu, Ni, Co, Fe and Mn indicated that combined variability due to local and procedural error averaged less than 5% of the total error and that precision estimates at the 95th percentile concentration value averaged less than 6.0%. Results presented indicate duplicates are more in accord with splits of individual samples (analytical duplicates) rather than separate field-site duplicates. This type of systematic approach provides a basis for interpreting geochemical trends within the survey area, while simultaneously allowing evaluation of the method of sampling and laboratory analysis. A procedure utilizing Duncan's Multiple Range Test examined the relationships between metal concentrations and class-interval and categorical observations of the drainage catchment, sample site and sediment sample. Results show that, many field observations can be systematically related to metal content of drainage sediments. Some elements are more susceptible than others to environmental factors and some factors influence few or many elements. For example, in sediments derived from granites there are significant relationships between bank type and concentration of 8 elements (Zn, Cu, Ni, Pb, Co, Fe, Mn and Hg). In contrast, the texture of these sediments, using estimates of fines contents as an index, did not significantly affect the concentration of any of the elements studied. In general, results indicate that groups of environmental factors acting collectively are more important than any single factor in determining background metal contents of drainage sediments. A procedure utilizing both a graphical and multiple regression approach was developed to identify and characterize anomalous samples. The procedure determines multivariate models based on background metal values which are used to describe very general geochemical relations of no interest for prospecting purposes. These models are then applied to sample subsets selected on the basis of factor/s known to strongly influence geochemical results. Individual samples are characterized after comparisons with relevant determined threshold levels and background multielemenmodels. One hundred and fifteen anomalous samples for zinc from seven provenance groups draining 1259 sample sites were identified and characterized by this procedure. Forty three of these samples had zinc concentrations greater than its calculated provenance threshold, while 72 of these anomalous samples were identified solely because their individual metal associations were significantly different than their provenance multivariate background model. The method provides a means to reduce the effects of background variations while simultaneously identifying and characterizing anomalous samples. The data analysis tools described here allow extraction of useful information from regional geochemical data, and as a result provide and effective means of defining problems of geological interest that warrant further investigation.