Three‐dimensional imaging of subsurface structural patterns using quantitative large‐scale multiconfiguration electromagnetic induction data

Electrical resistivity tomography (ERT) is a non-destructive geophysical method that provides images of the soil electrical resistivity. In particular, this study focuses on small-scale soil subsurface areas (up to 1 m deep). Soil resistivity depends on several factors, particularly soil water content. Consequently, ERT has proven to be effective in detecting water flow pathways during infiltration tests. ERT has already been used for hydroecological and hydrogeological applications, but its use still requires further investigation and new developments, particularly for specific processes such as preferential flows. Indeed, water infiltration into the soil is all but homogeneous with the occurrence of preferential flows due to several factors (lithological heterogeneity, macropores, cracks, macrofauna galleries, and root channels). The presence of these preferential flows promotes the downward movement of water and solutes to deeper soil horizons. Thus, the detection of these flows using geophysical methods, such as ERT, should provide a better understanding of the dynamics of preferential flows. However, conventional ERT inversion methods have proven unable to provide insight into the processes at adequate scales (e.g., the macropore scale) and have shown difficulties in detecting sharp variations because of smoothing constraints. Information from apparent resistivity may be lost because of these constraints.To overcome these limitations, an inversion method based on Convolutional Neural Networks (CNNs) is proposed to detect small-scale resistivity heterogeneities. For the training step, we designed a specific generator to produce synthetic resistivity data for various 2D random electrical resistivity distributions mimicking different types of soil heterogeneity (earthworm and root induced macropore, layering, etc.) and for typical protocols for ERT acquisition. For each case, our database associates the true resistivity field with the apparent resistivity. This database contains a large number of training pairs that allow machine learning.The preliminary results show that while some predictions were able to predict properly the soil heterogeneities (shape and size), the values of the estimated true resistivity were far from the target values. To avoid unrealistic estimates, we added physical constraints during the training process. An additional forward calculation was performed based on the true resistivities predicted by the neural network, then the apparent resistivities corresponding to the predicted resistivities were compared to the apparent resistivities corresponding to the targeted true resistivities and a supplementary loss function was added to the initial loss function. At this stage, the neural networks were trained on heterogeneous resistivity distributions in the soil with neither time evolution nor link to hydrological processes. In the future, the resistivity generator will be coupled with hydrological models to simulate water infiltration dynamics and changes in soil water content over time. This perspective is essential for applying the proposed method to detect flow pathways during infiltration tests.

Abstract. This paper presents a time-lapse application of electrical methods (electrical resistivity tomography, ERT; and mise-à-la-masse, MALM) for monitoring plant roots and their activity (root water uptake) during a controlled infiltration experiment. The use of non-invasive geophysical monitoring is of increasing interest as these techniques provide time-lapse imaging of processes that otherwise can only be measured at few specific spatial locations. The experiment here described was conducted in a vineyard in Bordeaux (France) and was focused on the behaviour of two neighbouring grapevines. The joint application of ERT and MALM has several advantages. While ERT in time-lapse mode is sensitive to changes in soil electrical resistivity and thus to the factors controlling it (mainly soil water content, in this context), MALM uses DC current injected into a tree stem to image where the plant root system is in effective electrical contact with the soil at locations that are likely to be the same where root water uptake (RWU) takes place. Thus, ERT and MALM provide complementary information about the root structure and activity. The experiment shows that the region of likely electrical current sources produced by MALM does not change significantly during the infiltration time in spite of the strong changes of electrical resistivity caused by changes in soil water content. Ultimately, the interpretation of the current source distribution strengthened the hypothesis of using current as a proxy for root detection. This fact, together with the evidence that current injection in the soil and in the stem produces totally different voltage patterns, corroborates the idea that this application of MALM highlights the active root density in the soil. When considering the electrical resistivity changes (as measured by ERT) inside the stationary volume of active roots delineated by MALM, the overall tendency is towards a resistivity increase during irrigation time, which can be linked to a decrease in soil water content caused by root water uptake. On the contrary, when considering the soil volume outside the MALM-derived root water uptake region, the electrical resistivity tends to decrease as an effect of soil water content increase caused by the infiltration. The use of a simplified infiltration model confirms at least qualitatively this behaviour. The monitoring results are particularly promising, and the method can be applied to a variety of scales including the laboratory scale where direct evidence of root structure and root water uptake can help corroborate the approach. Once fully validated, the joint use of MALM and ERT can be used as a valuable tool to study the activity of roots under a wide variety of field conditions.

Evaluation of soil water content in tilled and cover-cropped olive orchards by the geoelectrical technique

This article presents a tutorial of the bases for, and problems encountered with, the resistivity and induced polarization methods in geotechnical and environmental applications. It commences with a discussion of aqueous electrolytic conduction in rocks including consideration of the effects of temperature, rock texture, rock type, geological processes, and of the presence of clay minerals. Both electrode and membrane polarization in soils and rocks are described. The elementary theory for the resistivity and induced polarization methods is introduced via formulas for electrodes on homogeneous and layered half-spaces. The notion of apparent resistivity is presented. Vertical electric sounding is described in relation to curve types, inversion, equivalence, anisotropy, and correlation. Profiling with resistivity is briefly treated while combined sounding-profiling is treated in more detail for both the resistivity and induced polarization methods. The parameters used to describe the induced polarization phenomena are introduced. A brief discourse follows on data acquisition and processing, including design considerations for transmitters and receivers, electrodes, and wire logistics. A section on arrays and the factors involved in selecting an array provokes the disclosure that while their application in geotechnical and environmental studies usually is straightforward much remains to be learned about the resistivity and induced polarization methods in general. Specific topics requiring study are comparative studies of various arrays in (a) depth of exploration in sounding and in profiling, (b) resolution of horizontal structures, (c) sensitivity to depth, (d) sensitivity to lateral effects, (e) sensitivity to buried and surface topography, and (f) the effectiveness of focused arrays. References to recent significant publications on one-, two-, and three-dimensional forward and inverse interpretation procedures follow. Problems encountered with these methods are initially treated under the section on arrays and are expanded with specific reference to geologic noise and negative induced polarization effects. The advantages of focused arrays are illustrated. The paper concludes with nine representative examples of applications.

ERT and salinity – A method to determine whether ERT-detected preferential pathways in brackish water-irrigated soils are water-induced or an artifact of salinity

Carbon nanotube (CNT) wires are light-weight and robust alternatives to conventional metal conductors. The weight savings, increased flexure tolerance, and corrosion resistance of CNT conductors make them a viable solution for a variety of space, defense, and power transmission applications. An individual CNT has orders of magnitude greater electrical conductivity than conventional metal conductors, but this has not been realized in bulk CNT networks. Recently, the use of chemical dopants has resulted in bulk CNT wire conductivities approaching 10 MS/m. As the electrical conductivity of CNT wires continues to approach that of conventional metals, deployment of these CNT conductors will require an understanding of how these CNT conductors and chemical dopants behave during practical operation.In the present work, commercially scaled CNT wires are physically densified through radial drawing dies and chemically doped with KAuBr4 resulting in an improvement in electrical conductivity to greater than 1 MS/m, a 6x improvement compared to the as-received CNT wire. The current density at failure of CNT wires increases with KAuBr4 doping and densification by 67% to 35 MA/m2. The electrical performance retention is determined by applying increasing current densities with intermittent rest steps and low current I-V sweeps. The low current I-V sweeps allow for changes in electrical conductivity due to permanent material degradation caused by previous high current density exposure to be determined. The instantaneous electrical conductivity averaged over the last 5 seconds of each current “on” step is used to determine the temperature dependent effects on electrical conductivity caused by Joule heat during high current application. The KAuBr4 doped and densified samples experience no permanent change in initial electrical conductivity at current densities up to ~32 MA/m2, 4x greater than the as-received CNT wires.The enhanced electrical conductivity retention of KAuBr4 doped and densified CNT wires at high current density was further probed though an analysis of the thermal stability of these doped CNT conductors. Thermogravimetric analysis indicated that minimal degradation of the KAuBr4 dopant occurs prior to thermal oxidation of the CNT materials at 400 °C. A variety of KAuBr4 doping and 400 °C thermal oxidation procedures were performed on CNT wires to understand how thermal degradation of the dopant relates to changes in the electrical conductivity and high current density stability. Energy dispersive X-ray (EDX) spectroscopy further related the changes in electrical conductivity to the elemental spatial analysis of gold and bromine in the KAuBr4-doped CNT samples before and after 400 °C thermal oxidation. This work concludes that the thermal stability of KAuBr4 results in improved electrical conductivity and stability at high current densities. Trace bromine and gold nanoparticles are maintained at temperatures below the onset of CNT degradation, thus providing residual doping until ultimate CNT wire failure.Recently chemical dopants such as I2 and IBr have also emerged as premiere dopants to improve the electrical conductivity of bulk CNT networks. These dopants will be used to further explore the effect doping procedures and the presence of excess dopant have on the electrical conductivity and high current stability of doped CNT wires. Developing a relationship between dopant thermal stability and electrical conductivity retention will allow for the development of a mechanism explaining dopant degradation at high current densities.

A common practice used by the Germans and collaborators in World War II, as part of the Holocaust, was to use existing Jewish cemeteries as places for mass burial. Research was completed at the Old Jewish Cemetery in Riga, Latvia, the Livas Jewish Cemetery in Liepaja, Latvia, and the Zaliakalnis Jewish Cemetery in Kaunas, Lithuania. The Old Jewish Cemetery in Riga was adjacent to the Riga Ghetto and was used to bury individuals murdered in the ghetto. In Kaunas, an area of the Zaliakalnis Jewish Cemetery is devoid of grave stones, and literature sources and testimony indicate that this area was used for the mass burial of Jews from the Kaunas Ghetto and other mass killings. In Liepaja, the local Jewish Heritage Foundation believes that there are mass graves within the Livas Cemetery. Methodologies for this research include the use of a pulseEkko Pro 500-megahertz ground-penetrating radar (GPR) system. Electrical resistivity tomography (ERT) data were collected through a linear array of electrodes coupled to a direct current (DC) resistivity transmitter and receiver. Analysis of aerial photography and satellite images was also employed at each location. ERT and GPR data indicate three separate trench anomalies in the Old Jewish Cemetery in Riga. The presence of these anomalies corroborates Holocaust survivor testimony that bodies were buried in mass graves in that area. In the Zaliakalnis Jewish Cemetery in Kaunas, ERT and GPR data indicate an anomaly in the western part of the cemetery, and ERT data further indicate two other possible mass graves. In Liepaja, preliminary GPR analysis indicates an anomaly in a cleared section of the cemetery. Based on the presence of geophysical anomalies in all three cemeteries, which correlate with literature sources and Holocaust survivor testimony, there is a high probability that mass graves are present at each site. Future research directions include expanding the search areas in each cemetery, additional literature and testimony-based research, and the addition of other geophysical methodologies.

Subsurface stratigraphy interpretation often relies on sparse borehole data. Due to the inherent spatial variability and limited borehole data, uncertainty inevitably exists in the interpreted subsurface stratigraphy. Geophysical approaches such as electrical resistivity tomography (ERT) provide continuous subsurface data in the concerned cross-section. Though the reliability of the geophysical data derived is much lower than that of the solid borehole data, the continuous subsurface data obtained from geophysical investigations might be taken as a complement to the sparse borehole data in the subsurface stratigraphy interpretation. This paper proposes an innovative subsurface stratigraphy interpretation approach, which takes advantage of the high reliability of sparse borehole data and the abundance of ERT data. This approach is partially developed based on the random field approach recently advanced by the authors, and the relationship between ERT data and borehole stratigraphies is mapped with the algorithm of the support vector machine. The uncertainty of the interpreted subsurface stratigraphy arising from the random selection of the training and testing datasets (for training the mapping relationship between ERT data and stratigraphies) is analyzed by a “ bootstrapping” method. Furthermore, field tests of site investigation at four benchmark stratigraphic cross-sections are conducted, and high-quality ERT and borehole data are collected. Based on the high-quality site investigation data obtained, illustrative applications of the proposed approach are presented.

<p>A full understanding of the moisture regimes in agricultural soils is critical when considering a climatic future that is potentially both drier and hotter. The study of near-surface hydrodynamics necessitates a high temporal frequency of measurements to allow the capture of fast-moving processes. In addition to this, heterogeneities in soils, coupled with spatially variable moisture contents, mean that point sensors alone can miss valuable information when studying soil hydrodynamics.</p><p>The sensitivity of Electrical Resistivity Tomography (ERT) to soil water content means that it is ideally suited to studying soil hydrodynamics. As a non-invasive technique, it is able to effectively capture spatial heterogeneities, while repeating ERT measurements at short time intervals enables the monitoring of rapid soil moisture changes.</p><p>In order to study Conservation Agriculture (CA) - an agricultural technique shown to have increased water and heat stress resilience - we collect frequent ERT measurements (≤ daily) over a long period of time (> 2 years) using PRIME - a low-cost, low-power, ERT monitoring instrument developed by the British Geological Survey. Our equipment is permanently installed at three agricultural observatories in southern Africa (Malawi, Zimbabwe, and Zambia), and is complemented by many co-located point sensors monitoring soil temperature, water content, and matric potential.</p><p>We compare the hydrodynamics - derived from ERT data - found under CA, with those under conventional agricultural tillage methods, to better understand the root of CA’s resilience to hot and dry weather conditions. We use laboratory measurements together with the high number of co-located point sensor measurements to build pedological / geophysical relationships for each site, comparing those derived from laboratory scale samples to those derived from in-field measurements.</p>

Durusu Lake is the biggest and most important freshwater source supplying drinking water to the European side of Istanbul. In this study, electrical resistivity tomography (ERT) and transient electromagnetic (TEM) measurements were applied to detect a possible salt water intrusion into the lake and to delineate the subsurface structure in the north of Durusu Lake. The ERT and TEM measurements were carried out along six parallel profiles extending from the sea coast to the lake shore on the dune barrier. TEM data were interpreted using different 1-D inversion methods such as Occam, Marquardt, and laterally constrained inversion (LCI). ERT data were interpreted using 2-D inversion techniques. The inversion results of ERT and TEM data were shown as resistivity depth sections including topography. The sand layer spreading over the basin has a resistivity of 150–400 Ωm with a thickness of 5–10 m. The sandy layer with clay, silt, and gravel has a resistivity of 15–100 Ωm and a thickness of 10–40 m followed by a clay layer of a resistivity below 10 Ωm. When the inversion of these data is interpreted along with the hydrogeology of the area, it is concluded that the salt water intrusion along the dune barrier is not common and occurs at a particular area where the distance between lake and sea is very close. Using information from boreholes around the lake, it was verified that the common conductive region at depths of 30 m or more consists of clay layers and clay lenses.

Combined application of GPR and ERT for the assessment of a wall structure at the Heptapyrgion fortress (Thessaloniki, Greece)

Understanding the relative humidity (RH) response of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is critical for improving the stability of organic electronic devices and developing selective sensors. In this work, combined gravimetric sensing, nanoscale surface probing, and mesoscale optoelectronic characterization are used to directly compare the RH dependence of electrical and optical conductivities and unfold connections between the rate of water adsorption and changes in functional properties of PEDOT:PSS film. We report three distinct regimes where changes in electrical conductivity, optical conductivity, and optical bandgap are correlated with the mass of adsorbed water. At low (RH < 25%) and high (RH > 60%) humidity levels, dramatic changes in electrical, optical, and structural properties occur, while changes are insignificant in mid-RH (25 < RH < 60%) conditions. We associate the three regimes with water adsorption at hydrophilic moieties at low RH, diffusion and swelling throughout the film at mid-RH, and saturation of the film by water at high RH. Optical film thickness increased by 150% as RH was increased from 9 to 80%. Low frequency (1 kHz) impedance increased by ∼100%, and film capacitance increased by ∼30% as RH increased from 9 to 80% due to an increase in the film dielectric constant. Changes in electrical and optical conductivities concomitantly decrease across the full range of RH tested.

Electromagnetic induction (EMI) measurements return an apparent electrical conductivity that represents a weighted average of the electrical conductivity distribution over a certain depth range. Different sensing depths are obtained for different orientations, different coil offsets, and different frequencies, which, in principle, can be used for a multi‐layer inversion. However, instrumental shifts, which often occur in EMI data, prevent the use of quantitative multi‐layer inversion. Recently, a new calibration method was developed that uses electrical resistivity tomography (ERT) inversion results and returns quantitative apparent conductivity values. Here, we introduce an inversion scheme that uses calibrated EMI data and inverts for a two‐layer earth. The inversion minimizes the misfit between the measured and modeled magnetic field by a combined global and local search and does not use any smoothing parameter. Application of this new scheme to synthetic data demonstrates its efficacy in providing the required physical property information. Inversion of calibrated experimental EMI data using horizontal coplanar (HCP) and vertical coplanar (VCP) loop configurations, coil offsets of 1 and 1.22 m, and frequencies of 8 and 15 kHz provides lateral and vertical conductivity variations very similar to those observed in an elaborate ERT experiment. The inversion is verified using synthetic EMI data calculated from ERT data. Inverting quantitative EMI data using this two‐layer inversion enables the quantitative mapping of lateral and vertical electrical conductivity variations over large areas.

Two important mechanisms affect our ability to estimate solute concentrations quantitatively from the inversion of field-scale electrical resistivity tomography (ERT) data: (1) the spatially variable physical processes that govern the flow of current as well as the variation of physical properties in space and (2) the overparameterization of inverse models, which requires the imposition of a smoothing constraint (regularization) to facilitate convergence of the inverse solution. Based on analyses of field and synthetic data, we find that the ability of ERT to recover the 3D shape and magnitudes of a migrating conductive target is spatially variable. Additionally, the application of Archie's law to tomograms from field ERT data produced solute concentrations that are consistently less than 10% of point measurements collected in the field and estimated from transport modeling. Estimates of concentration from ERT using Archie's law only fit measured solute concentrations if the apparent formation factor is varied with space and time and allowed to take on unreasonably high values. Our analysis suggests that the inability to find a single petrophysical relation in space and time between concentration and electrical resistivity is largely an effect of two properties of ERT surveys: (1) decreased sensitivity of ERT to detect the target plume with increasing distance from the electrodes and (2) the smoothing imprint of regularization used in inversion.

Landslides occur worldwide. Global damages range in billions of dollars and cost hundreds of lives each year; Sweden is not an exception. In this study, we have acquired radiomagnetotelluric (RMT), electrical resistivity tomography (ERT) and high-resolution reflection seismic along 4 profiles with the main aim of imaging the geometry of quick clays and associated unconsolidated sediments that have caused landslides in a pilot study area in southwest Sweden. Comparison between the electrical resistivity models from the 2D inversions of RMT and ERT data with the reflections observed in the seismic data suggests a good correlation between the small-scale structures and those observed in the RMT model. However, the ERT model better delineates the resistive bedrock than the RMT model. The resistivity models are also compared with the CPT-R data collected in two geotechnical boreholes and further confirm some of the layer boundaries imaged with the acquired surface geophysical data.