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Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the 'Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3-D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Landslides pose significant risks to communities and infrastructure, and mitigating these risks relies on understanding landslide causes and triggering processes. It has been shown that geophysical surveys can significantly contribute to the characterization of unstable slopes. However, hydrological processes can be temporally and spatially heterogeneous, requiring their related properties to be monitored over time. Geoelectrical monitoring can provide temporal and volumetric distributions of electrical resistivity, which are directly related to moisture content. To date, studies demonstrating this capability have been restricted to 2-D sections, which are insufficient to capture the full degree of spatial heterogeneity. This study is the first to employ 4-D (i.e., 3-D time lapse) resistivity imaging on an active landslide, providing long-term data (3 years) highlighting the evolution of moisture content prior to landslide reactivation and showing its decline post reactivation. Crucially, the time-lapse inversion methodology employed here incorporates movements of the electrodes on the unstable surface. Although seasonal characteristics dominate the shallow moisture dynamics during the first 2 years with surficial drying in summer and wetting in winter, in the months preceding reactivation, moisture content increased by more than 45% throughout the slope. This is in agreement with independent data showing a significant rise in piezometric heads and shallow soil moisture contents as a result of prolonged and intense rainfall. Based on these results, remediation measures could be designed and early-warning systems implemented. Thus, resistivity monitoring that can allow for moving electrodes provides a new means for the effective mitigation of landslide risk.

In the broad spectrum of natural hazards, landslides in particular are capable of changing the landscape and causing significant human and economic losses. Detailed site investigations form an important component in the landslide risk mitigation and disaster risk reduction process. These investigations usually rely on surface observations, discrete sampling of the subsurface, and laboratory testing to examine properties that are deemed representative of entire slopes. Often this requires extensive interpolations and results in large uncertainties. To compliment and extend these approaches, we present a study from an active landslide in a Lias Group clay slope, North Yorkshire, UK, examining combined P- and S-wave seismic refraction tomography (SRT) as a means of providing subsurface volumetric imaging of geotechnical proxies. The distributions of seismic wave velocities determined from SRT at the study site indicated zones with higher porosity and fissure density that are interpreted to represent the extent and depth of mass movements and weathered bedrock zones. Distinguishing the lithological units was facilitated by deriving the Poisson's ratio from the SRT data as saturated clay and partially saturated sandy silts showed distinctively different Poisson's ratios. Shear and Young's moduli derived from the SRT data revealed the weak nature of the materials in active parts of the landslide (i.e. 25 kPa and 100 kPa respectively). The SRT results are consistent with intrusive (i.e. cone penetration tests), laboratory, and additional geoelectrical data from this site. This study shows that SRT forms a cost-effective method that can significantly reduce uncertainties in the conceptual ground model of geotechnical and hydrological conditions that govern landslide dynamics.

Measurement sensors permanently installed on landslides will inevitably change their position over time due to mass movements. To interpret and correct the recorded data, these movements have to be determined. This is especially important in the case of geoelectrical monitoring, where incorrect sensor positions produce strong artefacts in the resulting resistivity models. They may obscure real changes, which could indicate triggering mechanisms for landslide failure or reactivation. In this paper we introduce a methodology to interpolate movements from a small set of sparsely distributed reference points to a larger set of electrode locations. Within this methodology we compare three interpolation techniques, i.e., a piecewise planar, bi-linear spline, and a kriging based interpolation scheme. The performance of these techniques is tested on a synthetic and a real-data example, showing a recovery rate of true movements to about 1% and 10% of the electrode spacing, respectively. The significance for applying the proposed methodology is demonstrated by inverse modelling of 4D electrical resistivity tomography data, where it is shown that by correcting for sensor movements corresponding artefacts can virtually be removed and true resistivity changes be imaged.

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Copyright of Anaesthesiologie & Intensivmedizin is the property of DGAI e.V. - Deutsche Gesellschaft fur Anasthesiologie und Intensivmedizin e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)