Imaging heterogeneities with electrical impedance tomography: laboratory results

Electrical impedance tomography (EIT) is commonly used on site as a characterisation and monitoring tool. In the present work this technique has been applied at laboratory scale in order to investigate its capabilities in controlled conditions, with particular reference to the detection of anomalies in sandy samples. Various configurations have been studied, investigating heterogeneities due to variation of porosity, grain size distribution and clay content. The results show the great potential of EIT as an imaging tool in laboratory equipment to check sample homogeneity and to monitor processes during tests

County-Based Priority Assessment Methodology for Phasing of Wellhead Protection Programs

ABSTRACT-Setting priorities to schedule and implement wellhead protection programs for municipal and community drinking water supplies is presented in the framework of a general risk assessment approach. This includes a hazard identification procedure representing the likelihood of contaminants being released to the surface environment, a hydrogeologic vulnerability assessment representing the risk of contaminants entering the groundwater supply, and an impact assessment, strongly linked to the population at risk. A methodology was developed to aggregate information on a county basis for Minnesota. The resulting composite risk index map shows a number of counties in the central part of the state roughly following a line from the Twin Cities Metropolitan area along two major transportation axes to the St. Cloud and Fargo-Moorhead area, and toward the south to the Rochester-Austin area to which a high priority for phasing-in of the program is recommended. These counties emerge in addition to those in the southeastern karst area of Minnesota that traditionally have been identified as vulnerable areas

Two-Way Regionalized Classification of Multivariate Datasets and its Application to the Assessment of Hydrodynamic Dispersion

Zones of mixing between shallow groundwaters of different composition were unravelled by “two-way regionalized classification,” a technique based on correspondence analysis (CA), cluster analysis (ClA) and discriminant analysis (DA), aided by gridding, map-overlay and contouring tools. The shallow groundwaters are from a granitoid plutonite in the Fundão region (central Portugal). Correspondence analysis detected three natural clusters in the working dataset: 1, weathering; 2, domestic effluents; 3, fertilizers. Cluster analysis set an alternative distribution of the samples by the three clusters. Group memberships obtained by correspondence analysis and by cluster analysis were optimized by discriminant analysis, gridded over the entire Fundão region, and converted into “two-way regionalized classification” memberships as follows: codes 1, 2 or 3 were used when classification by correspondence analysis and cluster analysis produced the same results; code 0 when the grid node was first assigned to cluster 1 and then to cluster 2 or vice versa (mixing between weathering and effluents); code 4 in the other cases (mixing between agriculture and the other influences). Code-3 areas were systematically surrounded by code-4 areas, an observation attributed to hydrodynamic dispersion. Accordingly, the extent of code-4 areas in two orthogonal directions was assumed proportional to the longitudinal and transverse dispersivities of local soils. The results (0.7–16.8 and 0.4–4.3 m, respectively) are acceptable at the macroscopic scale. The ratios between longitudinal and transverse dispersivities (1.2–11.1) are also in agreement with results obtained by other studies

Versatile thinking and the learning of statistical concepts

Statistics was for a long time a domain where calculation dominated to the detriment of statistical thinking. In recent years, the latter concept has come much more to the fore, and is now being both researched and promoted in school and tertiary courses. In this study, we consider the application of the concept of flexible or versatile thinking to statistical inference, as a key attribute of statistical thinking. Whilst this versatility comprises process/object, visuo/analytic and representational versatility, we concentrate here on the last aspect, which includes the ability to work within a representation system (or semiotic register) and to transform seamlessly between the systems for given concepts, as well as to engage in procedural and conceptual interactions with specific representations. To exemplify the theoretical ideas, we consider two examples based on the concepts of relative comparison and sampling variability as cases where representational versatility may be crucial to understanding. We outline the qualitative thinking involved in representations of relative density and sample and population distributions, including mathematical models and their precursor, diagrammatic forms