Predicting the movements of permanently installed electrodes on an active landslide using time-lapse geoelectrical resistivity data only

If electrodes move during geoelectrical resistivity monitoring and their new positions are not incorporated in the inversion, then the resulting tomographic images exhibit artefacts that can obscure genuine time-lapse resistivity changes in the subsurface. The effects of electrode movements on time-lapse resistivity tomography are investigated using a simple analytical model and real data. The correspondence between the model and the data is sufficiently good to be able to predict the effects of electrode movements with reasonable accuracy. For the linear electrode arrays and 2D inversions under consideration, the data are much more sensitive to longitudinal than transverse or vertical movements. Consequently the model can be used to invert the longitudinal offsets of the electrodes from their known baseline positions using only the time-lapse ratios of the apparent resistivity data. The example datasets are taken from a permanently installed electrode array on an active lobe of a landslide. Using two sets with different levels of noise and subsurface resistivity changes, it is found that the electrode positions can be recovered to an accuracy of 4 % of the baseline electrode spacing. This is sufficient to correct the artefacts in the resistivity images, and provides for the possibility of monitoring the movement of the landslide and its internal hydraulic processes simultaneously using electrical resistivity tomography only

The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

Light-driven processes: key players of the functional biodiversity in microalgae

International audienc

Capacitive resistivity imaging with towed arrays

The capacitive resistivity (CR) technique is a generalization of the conventional DC resistivity method that facilitates measurements of electrical resistivity on engineered surfaces and highly resistive ground. The CR methodology allows the use of towed sensor arrays, thus enabling the rapid collection of high-resolution resistivity data. Under quasi-static conditions, CR data are equivalent to galvanic DC measurements so that CR datasets can be interpreted with conventional DC inversion algorithms. In this study, we demonstrate that the methodology and fundamental parameters of the CR technique facilitate spatial sampling at the centimeter scale for towing speeds of the order of 2.5 km/h. We argue that the dipole-dipole array is the most suitable geometry for dynamic CR measurements and present example data acquired with a prototype instrument using plate-wire combinations arranged in an equatorial geometry. The information content of raw CR data is found to be dominant over towing-induced noise and a direct comparison with DC profile data shows good agreement between both techniques. Based on these findings, we show that tomographic imaging is possible using datasets acquired with moving arrays. Closer investigation of the practical aspects of towed-array capacitive resistivity imaging (CRI) highlights the similarities with galvanic multi-electrode surveys, but the different geometric constraints and sampling regime of CRI give rise to advantages (high lateral resolution) as well as disadvantages (limitations in vertical resolution). We conclude our study with recommendations for practical CRI survey procedures and present a field example where we have successfully imaged a subsurface target in 3D. Towed-array CRI is found to provide equivalent (and in some ways superior) information about the shallow subsurface when compared to DC ERT (electrical resistivity tomography); it therefore widens the scope of electrical imaging surveys to environments where the conventional methodology would be impractical

Improved strategies for the automatic selection of optimized sets of Electrical Resistivity Tomography measurement configurations

Two strategies are presented for obtaining the maximum spatial resolution in electrical resistivity tomography surveys using a limited number of four-electrode measurement configurations. Both methods use a linearized estimate of the model resolution matrix to assess the effects of including a given electrode configuration in the measurement set. The algorithms are described in detail, and their execution times are analysed in terms of the number of cells in the inverse model. One strategy directly compares the model resolution matrices to optimize the spatial resolution. The other uses approximations based on the distribution and linear independence of the Jacobian matrix elements. The first strategy produces results that are nearer to optimal, however the second is several orders of magnitude faster. Significantly however, both offer better optimization performance than a similar, previously published, method. Realistic examples are used to compare the results of each algorithm. Synthetic data are generated for each optimized set of electrodes using simple forward models containing resistive and/or conductive prisms. By inverting the data, it is demonstrated that the linearized model resolution matrix yields a good estimate of the actual resolution obtained in the inverted image. Furthermore, comparison of the inversion results confirms that the spatial distribution of the estimated model resolution is a reliable indicator of tomographic image quality

Practical aspects of applied optimised survey design for electrical resistivity tomography

The use of optimised resistivity tomography surveys to acquire field data imposes extra constraints on the design strategy beyond maximising the quality of the resulting tomographic image. In this paper, methods are presented to 1) minimise electrode polarisation effects; 2) make efficient use of parallel measurement channels; and 3) incorporate data noise estimates in the optimisation process. 1) A simulated annealing algorithm is used to rearrange the optimised measurement sequences to minimise polarisation errors. The method is developed using random survey designs, and is demonstrated to be effective for use with single and multi-channel optimised surveys. 2) An optimisation algorithm is developed to design surveys by successive addition of multi-channel groups of measurements rather than individual electrode configurations. The multi-channel surveys are shown to produce results nearly as close to optimal as equivalent single channel surveys, while reducing data collection times by an order of magnitude. 3) Random errors in the data are accounted for by weighting the electrode configurations in the optimisation process according to a simple error model incorporating background and voltage-dependent noise. The use of data weighting produces optimised surveys that are more robust in the presence of noise, while maintaining as much of the image resolution of the noise-free designs as possible. All the new methods described in this paper are demonstrated using both synthetic and real data, the latter having been measured on an active landslide using a permanently installed geoelectrical monitoring system

Electrical resistivity tomography applied to geologic, hydrogeologic, and engineering investigations at a former waste-disposal site

A former dolerite quarry and landfill site was investigated using 2D and 3D electrical resistivity tomography (ERT), with the aims of determining buried quarry geometry, mapping bedrock contamination arising from the landfill, and characterizing site geology. Resistivity data were collected from a network of intersecting survey lines using a Wennerbased array configuration. Inversion of the data was carried out using 2D and 3D regularized least-squares optimization methods with robust (L1-norm) model constraints. For this site, where high resistivity contrasts were present, robust model constraints produced a more accurate recovery of subsurface structures when compared to the use of smooth (L2-norm) constraints. Integrated 3D spatial analysis of the ERT and conventional site investigation data proved in this case a highly effective means of characterizing the landfill and its environs. The 3D resistivity model was successfully used to confirm the position of the landfill boundaries, which appeared as electrically well-defined features that corresponded extremely closely to both historic maps and intrusive site investigation data. A potential zone of leachate migration from the landfill was identified from the electrical models; the location of this zone was consistent with the predicted direction of groundwater flow across the site. Unquarried areas of a dolerite sill were imaged as a resistive sheet-like feature, while the fault zone appeared in the 2D resistivity model as a dipping structure defined by contrasting bedrock resistivities