Sample Catchment Basin Research Articles

Geochemical atlas of the Medvednica Mt.: natural distribution of geochemical elements in stream sediments

The sample catchment basin approach applying the active stream sediment as a sampling medium is a frequently used cartographic technique for mapping geochemical data. It is particularly useful in mountainous areas with developed drainage network where each individual catchment basin can be assumed to represent an elementary map unit. Stream sediments have been widely used during the last two decades as an alternative sampling medium (vs. soils and overbank sediments) for regional geochemical exploration, mineral exploration, and geochemical mapping as well as for fingerprinting purposes and provenance studies. In this study, uninhabited slopes of the Medvednica Mt. in the close vicinity of the Croatian capital Zagreb, including the whole Medvednica Nature Park, have been selected as an appropriate geochemical environment for evaluation of geochemical baselines at the local and regional scale. The single-element geochemical maps representing the spatial distribution of 21 elements (As, Ba, Ca, Co, Cu, K, La, Mg, Mn, Na, Nb, Ni, P, Pb, Sc, Sr, Th, Ti, V, Y, and Zn) reflect both natural and anthropogenic impact on the environment at the contact of urban and natural landscapes.

Catchment basin modelling of stream sediment anomalies revisited: incorporation of EDA and fractal analysis

ABSTRACT This paper revisits catchment basin modelling of stream sediment geochemical anomalies with regard to two aspects: (1) standardization of uni-element residuals derived from analysis of a number of subsets of stream sediment geochemical data in order to obtain a single set of uni-element residuals for classification of anomalies; and (2) objective classification of anomalies in dilution-corrected uni-element residuals and in derivative scores representing multi-element associations. These two aspects of catchment basin modelling of stream sediment geochemical anomalies were examined in the Aroroy epithermal-Au district (Philippines). For the first aspect, the results of the case study show that, for the standardization of dilution-corrected uni-element residuals per data subset in order to derive a single set of dilution-corrected uni-element residuals for classification of anomalies, the application of robust statistics in exploratory data analysis is preferable to the application of classical statistics in confirmatory data analysis. For the second aspect, the results of the case study show that anomalies in standardized dilution-corrected uni-element residuals and in derivative scores representing multi-element associations can be identified objectively by application of the concentration-area fractal analysis. The results of the case study further show that the area of individual sample catchment basins is useful in GIS-based screening of significant anomalies by integrating derivative geochemical variables with fault/fracture density, which was estimated as the ratio of number of pixels representing faults/fractures in a sample catchment basin to number of pixels in the same sample catchment basin.

Mapping of anomalies in continuous and discrete fields of stream sediment geochemical landscapes

ABSTRACT In this study, continuous field models of geochemical landscapes were obtained by interpolating stream sediment geochemical data while discrete field models of geochemical landscapes were obtained by attributing stream sediment geochemical data to their sample catchment basins. This study aimed to: (1) compare and contrast anomaly maps derived from continuous and discrete field models of stream sediment geochemical landscapes; and (2) determine which empirical frequency distributions – those of original point data or those of pixels values in models of stream sediment geochemical landscapes – are more useful in mapping of anomalies in such geochemical landscapes. Anomalies were mapped by using the mean+2 SDEV (standard deviation), median+2 MAD (median absolute deviation) and concentration–area (C–A) fractal methods of identifying threshold values in a geochemical data set. The results of the study in the Aroroy gold district (Philippines) highlight the following findings. In mapping of anomalies in either continuous or discrete field models of stream sediment geochemical landscapes, the C–A fractal method performs best, followed by the median+2 MAD method and then by the mean+2 SDEV method. Anomalies mapped in discrete field models, compared to anomalies mapped in continuous field models, of stream sediment geochemical landscapes mostly have stronger positive spatial associations with the known epithermal Au deposit occurrences in the study area. Empirical frequency distributions of either the original point data or the pixels values in the models of stream sediment geochemical landscapes are similarly useful in applying the C–A fractal method, but not in applying either the median+2 MAD or mean+2 SDEV method, to map anomalies in either continuous or discrete field models of such geochemical landscapes.

Geochemical mapping using a geomorphologic approach based on catchments

The Extended Sample Catchment Basin (ESCB) mapping technique, discussed in this paper, can be used to display the spatial distribution of geochemical variables measured in stream sediments taking into consideration the geomorphologic settings and the hydrographic patterns of surveyed areas. This approach is based on the association of an area of statistical representativeness with each sample, and on the assumption that the concentrations measured in the stream sediments can be considered as average reference values for this area. ESCBs can be easily identified considering the position of the sampling points within the hydrographic network and using the confluences between the streams of highest rank as break points for representing changes of the geochemical background. This approach, different from the traditional geostatistical and deterministic ones, does not consider the Euclidean distance among the sampling points as a measure of geochemical similarity but only refers to their functional relationship along the streams (following the water and the sediment flow) to measure their proximity. ESCBs can be seen as a specific development of previous techniques based on catchments and proves to be especially useful for supporting land planning in a preliminary survey phase while it is not specifically suitable for the identification of point sources of geochemical anomalies. Due to the fractal nature of the hydrographic network, all the procedures can be driven in a GIS environment by using digital terrain models apart from their spatial resolution.

Recognition of areas of anomalous concentration of potentially hazardous elements by means of a subcatchment-based discriminant analysis of stream sediments

The statistical technique of discriminant analysis associated with the calculation of an information coefficient has been applied to the concentrations of 37 chemical elements for calculating the mixing of stream sediments of different origin in the Mignone river basin. Discriminant analysis has been based on sample catchment basins (SCBs), defined as the part of the drainage basin between two consecutive sampling points along the same stream branch, and on the identification of 4 different litho-geochemical groups. This approach, has been used to define the membership probability values for every sample by applying Bayes' rule and calculating posterior probability. The grade of uncertainty for each group assignment has been evaluated by using an information coefficient, based on a classification entropy index, and running a procedure analogue to that used for processing membership values in fuzzy analysis. The maximum theoretical concentration that can be expected in soils near the sampling point ( enhanced concentration) has then been calculated from both the measured and the membership values by introducing a specific enhancement function. Theoretical background concentrations at every sampling point have been also calculated by weighting the average value of concentration in each group with the membership values for each sample. These have been successively compared with the measured and enhanced concentrations to identify anomalous areas. The distribution maps of Arsenic and Vanadium in the Mignone River basin (central Italy) have been drawn accordingly to this technique, leading to the identification of areas of potential risk for human health.

Cartographic techniques for mapping the geochemical data of stream sediments: the ?Sample Catchment Basin? approach

The Sample Catchment Basin (SCB) mapping technique extends the representativeness of the geochemical features of stream sediments to the surface of the whole upstream drainage basin. SCB boundaries clash with the water divides traced from each sampling point and are limited upstream by the presence of further SCBs. They are also assumed to represent the elementary map unit. The rank of SCBs can be defined counting the number of upstream SCBs along the branches of a fluvial network. The presence of low rank SCBs minimizes the statistical redundancy of measures. The SCB technique is particularly suitable for the geochemical mapping of mountainous or hilly areas and to correctly display the information into a morphological context. This approach can be also valuable in the case of low sampling density, inhomogeneous sampling schemes, and especially when very accurate evaluations of the spatial distribution of chemicals (with natural or anthropogenic origin) are required.

A catchment basin approach to the analysis of reconnaissance geochemical-geological data from Albay Province, Philippines

A systematic approach for identifying mineral exploration target areas from reconnaissance stream sediment data without sufficient a-priori control information has been demonstrated in a portion of western Albay Province in the southern Bicol Peninsula of the Philippines. The approach involved devising a rapid method of catchment basin mapping using a geographic information system (GIS) so that the areal influence of the catchment basins may be incorporated in the geochemical data analysis. Areal proportions of mapped rock units occurring in the sample catchment basins and observed Mn and Fe contents in stream sediments are used as independent variables in multiple regression analysis to predict element contents in stream sediments related to lithologic and chemical controls. The predicted element contents are filtered-out from the original data to leave residuals in which the effects of other factors (e.g., mineralization) may be seen. A simple correction for the effects of downstream dilution is applied; this allows for the different sizes of the sample catchment basins so that positive geochemical residuals are enhanced. The inter-relationship of the different positive residuals in ‘highly enriched’ samples are investigated through principal components analysis to determine and quantify an ‘anomalous geochemical signature’. Lastly, the ‘anomalous geochemical signature’ is integrated with ‘proximity’ to faults/fractures to determine favourable target areas. For the test region, the lithologic controls explain between 80% and 100% of the variability in most of the elements studied. Chemical controls account for generally less than 5% of the variability in the data. Most of the dilution-corrected residuals reveal high relative enrichment in certain areas underlain by andesite and/or diorite. An anomalous Cu-Mg-Fe-Zn geochemical signature is disclosed by the principal components analysis of the dilution-corrected residuals in ‘highly enriched’ samples. Most sample catchment basins defined by this ‘anomalous geochemical signature’ pertain to areas underlain by andesitic rocks. Integration of the ‘anomalous geochemical signature’ and ‘proximity’ to faults/fractures reveals that some of these anomalous sample catchment basins are favourable target areas. These areas are interpreted to contain andesite-hosted stockwork or stringer zones that once formed part of a complete stratigraphic sequence of a volcanogenic massive sulphide occurrence. The results demonstrate the usefulness and ability of the procedures followed to extract significant anomalies from the reconnaissance geochemical data without the benefit of sufficient a-priori control data to aid in anomaly recognition. Similar procedures could also be applied elsewhere.