Impedance Tomography Research Articles

Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment

Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment

Sensitivity Matrix Update Method for Electrical Resistance Tomography Based on Error-Constrained Cross Fusion Residual Attention Network

Abstract Electrical resistance tomography (ERT) is an imaging technique of conductivity distribution. The image reconstruction algorithm based on the empty field sensitivity matrix is widely used because it provides an approximate solution to the complex ERT inverse problems. However, due to the soft field effect, the sensitivity matrix changes with the media distribution, leading to significant errors in image reconstruction. To address this issue, an error-constrained deep learning scheme for bubble flow, namely cross fusion residual attention network (CFRA-Net) is designed to update the sensitivity matrix during gas-liquid-solid fluidized bed operation. CFRA-Net employs a multi-head self-attention mechanism to enhance bubble features in boundary measurements, a multilevel cross fusion module to fuse empty field strength and boundary measurement information, and a novel serial-channel residual spatial attention block to boost the feature extraction capability of the model. A weighted loss function is designed to give more weight to the gas phase distribution region. Additionally, this paper establishes a dataset for gas-liquid-solid three-phase flow, considering background field conductivity variations. Validation and reliability of the proposed method are assessed through ablation, comparison, and noise experiments. The experimental results demonstrate that CFRA-Net achieves rapid updates of the sensitivity matrix, high imaging accuracy, and robust noise immunity.

Comprehensive geophysical, geotechnical, and geochemical assessments of an offshore landfill in Singapore

Comprehensive site investigation techniques, including Electrical Resistivity Tomography (ERT), Induced Polarization (IP), Multichannel Analysis of Surface Waves (MASW), and Microtremor Array Method (MAM), were integrated with geotechnical and geochemical tests of retrieved waste samples from Singapore’s operational offshore landfill. The properties of landfill wastes vary widely, including shear-wave velocities 127–248 m/s, densities 1.2–2.1 Mg/m3, resistivity 3.0–25.3 Ω∙m, and chargeability 48–82 mV/V. The natural clay layer underneath was clearly delineated and effectively mitigated leachate leakage. K-means clustering of the geophysical data facilitates precise mapping of waste distribution and quantities of recoverable metals based on quantitative criteria. This study illustrates a thorough case study adopting the new site investigation and characterization paradigm for an offshore landfill, which provides insights into leachate leakage detection and evaluations of landfill mining and resource recovery.

Integrated Geophysical Investigation using Aero-radiometric and Electrical Methods for Potential Gold mineralization within Yauri/Zuru Schist Belts, Kebbi State NW Nigeria

This study used aero-radiometric, 2D electrical resistivity tomography (ERT), and induced polarization (IP) methods to delineate gold mineralization potential. The study also confirmed and followed-up on regions with major structural features identified in previous aeromagnetic studies in the area. A half-degree airborne radiometric data of sheet 118_Yelwa from the NGSA, which contains three radioelements (%K, eTh, and eU) were used in this study. These datasets were processed and analyzed with Oasis Montaj Grid Math expression builder to obtain the %K_ratio_eTh and Ternary grid anomalies. The results identified zones E and F as hydrothermally altered regions that may harbour gold mineralization. These findings were consistent with the regions of major structural features identified in previous aeromagnetic studies in the area. The zones were located in the eastern parts of Ngaski, Yauri (Yelwa), Shanga, and Agwara, as well as Magama's northwest region. However, zone F1 (the eastern portion of Ngaski/Yauri) has been further investigated using 2ERT and IP detailed geophysical methods in a dipole-dipole configuration. The results of geoelectric techniques along profiles 1, 2, and 3 identified the major gold mineralization potential zones, which were labeled A1, A, and C. These regions have low/high resistivity and chargeability signatures, and could thus be interpreted as potential target zones for metallic mineral exploration, particularly gold mineralization. The regions are located in the northern part of Mararraba and southwest of the Jinsani areas of Kebbi State.

Quantification of soil water content by machine learning using enhanced high-resolution ERT

The accurate acquisition of soil water content is a fundamental cornerstone of research into hydrological processes and agricultural engineering. Electrical Resistivity Tomography (ERT) has been validated for hydrological studies and soil monitoring. The establishment of a quantitative relationship between ERT resistivity data and soil water content is usually based on rock physics models. However, the applicability of such models in complex environments and the acquisition of the relevant parameters pose a certain challenge. In addition, the spatial resolution of ERT limits its application in soil moisture assessment. Therefore, a machine learning-based approach is proposed in this study to determine the quantitative relationship between resistivity and soil water content. We investigate the integration of three machine learning models (KNN, RF, XGBOOST) with ERT to predict the water content of clay soils. The results show that the RF model achieves an R2 of 0.92 with an RMSE of 0.41. To improve the ERT resolution, a new data collection method (MRU) is introduced in this study by increasing the density of ERT data collection. A comparative analysis is conducted between traditional ERT data collection methods and the MRU approach in terms of soil water content prediction accuracy. The results show that the MRU method of data collection improves the accuracy of soil water content prediction by an average of 57% compared to traditional methods. This study confirms the feasibility of using machine learning models to establish mappings between resistance and water content and shows that the MRU data collection method for ERT effectively improves the accuracy of predicting soil water content. These results provide a new perspective for hydrological process research and agricultural monitoring technology.

Employing automated electrical resistivity tomography for detecting short- and long-term changes in permafrost and active-layer dynamics in the maritime Antarctic

Abstract. Repeated electrical resistivity tomography (ERT) surveys can substantially advance the understanding of spatial and temporal freeze–thaw dynamics in remote regions, such as Antarctica, where the evolution of permafrost has been poorly investigated. To enable time-lapse ERT surveys in Antarctica, an automated ERT (A-ERT) system is required, as regular site visits are not feasible. In this context, we developed a robust A-ERT prototype and installed it at the Crater Lake CALM-S site on Deception Island, Antarctica, to collect quasi-continuous ERT measurements. We developed an automated data processing workflow to efficiently filter and invert the A-ERT datasets and extract the key information required for a detailed investigation of permafrost and active-layer dynamics. In this paper, we report on the results of two complete year-round A-ERT datasets collected in 2010 and 2019 at the Crater Lake CALM-S site and compare them with available climate and borehole data. The A-ERT profile has a length of 9.5 m with an electrode spacing of 0.5 m, enabling a maximum investigation depth of approximately 2 m. Our detailed investigation of the A-ERT data and inverted results shows that the A-ERT system can detect the active-layer freezing and thawing events with high temporal resolution. The resistivity of the permafrost zone in 2019 is very similar to the values found in 2010, suggesting the stability of the permafrost over almost 1 decade at this site. The evolution of thaw depth exhibits a similar pattern in both years, with the active-layer thickness fluctuating between 0.20–0.35 m. However, a slight thinning of the active layer is evident in early 2019, compared to the equivalent period in 2010. These findings show that A-ERT datasets, combined with the new processing workflow that we developed, are an effective tool for studying permafrost and active-layer dynamics with very high resolution and minimal environmental disturbance. The ability of the A-ERT setup to monitor the spatiotemporal progression of thaw depth in two dimensions, and potentially in three dimensions, and to detect brief surficial refreezing and thawing of the active layer reveals the significance of the automatic ERT monitoring system to record continuous resistivity changes. An A-ERT monitoring setup with a longer profile length can investigate greater depths, offering effective monitoring at sites where boreholes are costly and invasive techniques are unsuitable. This shows that the A-ERT setup described in this paper can be a significant addition to the Global Terrestrial Network for Permafrost (GTN-P) and the Circumpolar Active Layer Monitoring (CALM) networks to further investigate the impact of fast-changing climate and extreme meteorological events on the upper soil horizons and to work towards establishing an early warning system for the consequences of climate change.

Identifying potential artificial recharge zone in an arid craton

Identifying sustainable artificial recharge zones in arid cratons is challenging due to complex geology and limited natural recharge conditions, making accurate site selection and management difficult. This study integrates Vertical Electrical Sounding (VES), the Analytic Hierarchy Process (AHP), and Boolean analysis to identify sustainable artificial recharge zones in the arid Bundelkhand craton of India. Aquifer thickness and fractures emerged as critical determinants of groundwater recharge conditions, revealing varying degrees of suitability for recharge across the study area. Approximately 2.31% (13.36 km2) of the area along streams exhibited "very high" suitability, while 8.09% (45.82 km2) had "high" suitability. “Moderate" suitability covered 17.86% (101.66 km2), "low" suitability accounted for 38.85% (218.39 km2), and "very low" suitability represented 17.35% (98.75 km2) of the area. Recharge potential was highest in the northeast and central parts, with the middle of the watershed exhibiting the lowest potential. The study demonstrated that this integrated approach significantly improved precision from 71.40% to 85.70% and enhanced the F1 score from 0.833 to 0.923, surpassing the performance of the AHP method alone. The findings highlighted the importance of strategic selection and targeting of specific locations for artificial recharge, as only ∼18% of the study area was suitable for such efforts, despite ∼43% showing potential for groundwater. AHP with VES proves more precise and reliable than Fuzzy-AHP with VES, with AHP's conservative approach classifying 55.70% of the area as very low to low suitability compared to Fuzzy-AHP's 41.92%, ensuring only the most suitable sites are selected. VES offers cost-effectiveness, noninvasiveness, and rapid generation of a 1D subsurface model, balancing its lower detail compared to Electrical Resistivity Tomography. When combined with the AHP, VES enhances adaptability to changing conditions, emphasizing ecological preservation and climate change resilience. This approach effectively addresses water challenges in arid regions, contributing to sustainable water resource management.

Permafrost Hydrogeology of Taylor Valley, Antarctica: Insights From Deep Electrical Resistivity Tomography

AbstractGlobal warming has prompted globally widespread permafrost thawing, resulting in enhanced greenhouse gas release into the atmosphere. Studies conducted in the Northern Hemisphere reveal an alarming increase in permafrost thawing. However, similar data from Antarctica are scarce. We conducted a 2‐D Deep Electrical Resistivity Tomography (DERT) survey in Taylor Valley, Antarctica, to image the distribution of permafrost, its thicknesses, lower boundaries, and hydrogeology. Results show resistive, discontinuous domains that we suggest represent permafrost units. We also find highly conductive layers (5–10 Ω·m), between 300–350 m and 600–650 m below ground level and a shallower (∼50–100 m depth) conductive layer. The combined data set reveals a broad brine system in Taylor Valley, implying multi‐tiered groundwater circulation: a shallow, localized system linked with surface water bodies and a separate deeper, regional circulation system. The arrangement of these brines across different levels, coupled with the uneven permafrost distribution, underscores potential interplay between the two systems.

Assessment of Hydrocarbon Contamination Using 2D Resistivity Imagining Method and Geochemical Analysis in Ibadan, Southwestern Nigeria

The study examined the use of 2D resistivity imaging survey and geochemical analysis to map and assess the level of soil contamination due to hydrocarbon spillage in Araromi Auto Spare Parts Market Ibadan, Southwestern Nigeria. The objectives are to provide 2D inverted resistivity sections beneath the study area, delineate anomalously low resistivity zones indicative of long-term hydrocarbon contamination in the sections, and determine concentrations of Polycyclic Aromatic Hydrocarbons (PAHs) in the suspected soils. Five traverses were run using Wenner array with electrode spacing varied from 5 m to 15 m and station increment of 5 m. The resistivity data were processed by using 2D inversion procedure to generate the 2D inverted resistivity sections. Geochemical analysis was conducted on five soil samples collected at 1 m depth in the low resistivity zones delineated on the 2D inversion sections, to determine the concentration of Polycyclic Aromatic Hydrocarbons (PAHs) to assess the level of contamination. The 2D inverted sections delineated low resistivity anomalies, ranging from 1.25 Ωm to 5.54 Ωm, characteristic of mature biodegraded hydrocarbon contamination. The results of geochemical analysis revealed total PAH concentration of 1390 µg/kg to 16140 µg/kg suggesting that the study area is heavily contaminated by the used motor oil. The combined use of 2D resistivity imaging and geochemical analysis has shown that soils beneath the study area has been heavily contaminated by the used motor oil, and may constitute potential health risk to the soil and groundwater systems in its vicinity. The results are expected to serve as useful guide in planning remediation programme.

Electrical Resistivity Tomography study above inaccessible old mine workings for safe erection of high voltage electricity power transmission terrestrial towers: a case study

Electrical Resistivity Tomography study above inaccessible old mine workings for safe erection of high voltage electricity power transmission terrestrial towers: a case study

The use of electrical resistivity tomography method to resolve land boundary disputes in mining areas

This paper presents the use of electrical resistivity tomography data to solve lingering land disputes arising from boundary encroachment by artisanal and small-scale miners in Jos, Plateau State. Seven electrical resistivity tomography (ERT) profiles were employed using the Wenner Alpha array with an electrode spacing of 1m. The 2Delectrical resistivity tomography image showed areas with low resistivity ranging from 1.80 to 250 Ωm that are interpreted as void or saturated mine drift, in contrast, areas with greater than 250 Ωm areas interpreted as dry mine drifts dug by artisanal miners in search of tin. The results revealed 38 mining drifts at depths ranging from 0 to 30m. Evidence from the 2D ERT method proves that underground mine cavities were created by mining drifts at the fringes of landed property. Field evidence of land subsidence appearing as sinkholes on the encroached property is also an indication of underground mining activities within the property. Mining activities within built-up areas damage soil conditions and pose a threat to buildings and infrastructure. The electrical resistivity tomography method employed in this study provides substantial technical proof for resolving land encroachment disputes in mining areas within Jos and its environs.

Detection of archaeological structure on the slope ground using geophysical methods: The case of the Castle of Canossa

Canossa Castle is located in the municipality of Canossa 18 km South of Reggio Emilia (North Italy). It was constructed in 940 by Adalberto Atto, son of Sigifredo of Lucca. Lombard chieftains needed this strategic hill to defend their lands against intrusions of other barbarian tribes. Subsequent improvements made the stronghold one of the best-defended castles in the country. Canossa Castle became particularly famous as a site of reconciliation between King Henry IV and Roman Pope Gregory VII during the Investiture Controversy in 1077.To redevelop the area and create an easy tourist route, the Superintendence of Archaeology, Fine Arts and Landscape for the Metropolitan City of Bologna and the Provinces of Modena, Reggio Emilia and Ferrara planned excavations in the area close to the Castle. To get precise information on where to carry out excavations geophysical surveys were undertaken in the spring of 2021. The castle stands on a rock with a steep slope and dense vegetation and this makes it very difficult to carry out geophysical prospecting. This guided the choice of geophysical methodologies to be used. For this reason, electrical resistivity tomography was used along the steep slope, while in the narrow flatter area, the ground penetrating radar methodology was used. The results demonstrate the effectiveness of the chosen geophysical methodologies.

Electrical resistivity imaging of crude oil contaminant in coastal soils – A laboratory sandbox study

Characterizing the subsurface distribution of crude oil after a spill in a coastal environment is challenging due to variations in the soil and fluid properties. In situ sampling is limited in capturing the lateral and vertical migration of the crude oil within the vadose and saturated zones. This study presents a laboratory sandbox framework used to assess the effectiveness of electrical resistivity imaging for investigating the spatiotemporal distribution of crude oil in coastal sandy soils. A sandbox with dimensions L = 240 cm, W = 60 cm, and H = 60 cm was constructed using a 10 mm plexiglass and filled to a 40 cm height with 2 mm medium to fine-grained sand. At each stage of the experiment, 20 kg of sand was mixed with 1 l of water to create moist sand, after which the mixture was flushed over 12 h to remove suspended fine particles. Both saturated and unsaturated conditions were simulated by setting the water table at 10 cm and draining a fully saturated system overnight. Two liters of crude oil were spilled and monitored for 30 h. A surface array of 98 electrodes, with a unit electrode spacing of 2 cm, was installed along two transects 12 cm apart. Resistivity measurements were collected using a dipole-dipole array before, during, and after the simulated crude oil spill. The time-lapse electrical resistivity results revealed an initial gravity-induced vertical migration under both saturated and unsaturated conditions; over time, lateral migration of crude oil became apparent. In the saturated zone, there was a noticeable reduction in the percentage difference in resistivity from 700 % to 400 % after 24 h, depicting a spatial and temporal redistribution of the crude oil attributed to variation in pore geometry. This highlights the sensitivity of electrical resistivity measurements to subtle but measurable anisotropy in the distribution of soil pores. Overall, electrical resistivity proved successful in imaging the non-ideal behavior of crude oil pollutants and the associated spatial changes in the pore-size distribution of subsurface sediments.

An Integrated Hydrogeophysical Approach for Unsaturated Zone Monitoring Using Time Domain Reflectometry, Electrical Resistivity Tomography and Ground Penetrating Radar

Continuous measurements of soil moisture in the deeper parts of the unsaturated zone remain an important challenge. This study examines the development of an integrated system for the continuous and 3-D monitoring of the vadose zone processes in a cost- and energy-efficient way. This system comprises TDR, ERT and GPR geophysical techniques. Their capacities to adequately image subsurface moisture changes with continuous and time-lapse measurements are assessed during an artificial infiltration experiment conducted in a characteristic urban site with anthropogenic fills and much compaction. A 3-D array was designed for each method to expand the information of a single TDR probe and obtain a broader image of the subsurface. Custom spatial TDR probes installed in boreholes made with a percussion drilling instrument were used for soil moisture measurements. Moisture profiles along the probes were estimated with a numerical one-dimensional inversion model and a standard calibration equation. High conductivity water used during all infiltration tests led to the detection of the flow by all techniques. Preferential flow was present throughout the experiment and imaged sufficiently by all methods. Overall, the integrated approach conceals each method’s weaknesses and provides a reliable 3-D view of the subsurface. The results suggest that this approach can be used to monitor the unsaturated zone at even greater depths.

Variogram models reconstruction for damaged ERT profiles

Reconstructing signals which are embedding spatial patterns such as Electrical resistivity tomography, is a process that should require to reconstruct first the spatial correlation of the damaged signals. This paper proposes an approach that implements an Unstationary Kriging (UNK) to reconstruct the experimental variogram of a damaged synthetic pseudo section within a set of pseudo sections coming from the same survey. We used and compared 02 other simple methods which are Linear Regression (LR) and Ordinary Kriging (OK), to test the hypothesis we formulate to link the experimental variograms coming from the same ERT survey. We implemented the UNK using Discrete Fourier Transforms (DFT) for trend modeling. After an implementation of the hybrid process (UNK) on 02 sets of data which are synthetics, we observed that the LR and the UNK methods present an interest. They both reconstruct signals with a +90% rate of accuracy, but when there is no structure or spatial correlation within the data, the LR is unstable. DFT was also tested alone for reconstruction but was mainly used in this study to help in computing the trends for each set of variographic signals. In the end, we conclude on an evidence that is: the proposed hybrid process is a promising way to reconstruct variographic signals, since we can improve it after more time invested to dig deep into the modeling of each of his components.

Structural Health Monitoring of Glass Fiber-Reinforced Polymer Laminates with Carbon Nanotube-Coated Glass Fiber Sensing Layer after Low-Velocity Impact Using Electrical Resistance Tomography

Structural health monitoring (SHM) of composite materials is of great significance in various practical applications. However, it is a challenge to accurately monitor the damage of composites without affecting their mechanical properties. In this paper, an embedded sensing layer based on carbon nanotube-coated glass fiber is designed, combined with electrical resistance tomography (ERT) for in situ damage monitoring. Multi-wall carbon nanotube-coated glass fiber (MWCNT-GF) is prepared and embedded into laminates as an in situ sensing layer. Low-velocity impact experiments demonstrate that the embedded sensing layer has high compatibility with the composite laminates and has no adverse effect on its impact response; although, the energy absorption behavior of glass fiber-reinforced polymer (GFRP) laminates containing MWCNT-GF occurs about 10% earlier than that of GFRP laminates overall. ERT technology is used to analyze the laminates after a low-velocity impact test. The results show that the in situ monitoring method with the embedded MWCNT-GF sensing layer can achieve high precision in imaging localization of impact damage, and the error of the detected damage area is only 4.5%.

Persistent post-flood hillslope activity posing a potential landslide dam hazard in the Ahr valley, Germany

BackgroundExtreme floods are known to severely reorganise inhabited landscapes by inundation, clogging, scouring and damaging infrastructure and lives. However, their post-event impacts are poorly understood, especially concerning coupled hillslope channel feedbacks such as the reactivation of slope instabilities connected to the river and that may be able to block it upon sudden failure. The July 2021 Ahr valley flood exemplified this ability of concurrent and sustained landscape reorganisation. Here, we study a retrogressive slope instability near the town of Müsch, in the upper Ahr valley using field mapping, repeat airborne laser scanning, electrical resistivity tomography and passive seismic monitoring to reveal the failure geometry, its mechanisms and transient activity.ResultsThe old landslide developed in lower Devonian rocks. It is 100 m wide, 200 m long and approximately 15–20 m deep, which leads to a total volume of about 430,000 m3. This landslide was severely undercut by the 2021 flood with 7000 m3 of material eroded at the landslide toe. The landslide has started to react. Given the narrow section of the river at this location, there is a potential landslide dam hazard. We modelled the inundation volumes and back fill times for different failure scenarios, ranging between 20,000 m3 and 330,000 m3 accumulating within 5 min and 20 h.ConclusionsOur results imply a need to systematically screen flood impacted landscapes for sustained post-event hillslope activity that governs hillslope-channel coupling, driving both persistent sediment injection into the stream and sudden river blocking and subsequent damming.

Cross-gradient joint inversion and clustering of ERT and SRT data on structured meshes incorporating topography

Summary The combination of electrical resistivity and seismic refraction tomography is a common practice for the characterization of subsurface features. Presently, the cross-gradient inversion scheme stands out as one of the most robust joint approaches, and some authors modified it to manage complex topographies on unstructured meshes even if at the expense of introducing additional parameters in the inversion process. We propose in this work a cross-gradient algorithm for jointly inverting electrical and seismic tomographic data on structured meshes in cases with non-flat topography. The proposed approach preserves the benefit of the classical cross-gradient approach without the need to impose physical length scales, as for irregular meshes. The quality of the results is evaluated in comparison with independent inversion through a new standardized cross-gradient index and a fuzzy c-means analysis that provides an assessment of the reconstruction accuracy through the membership function. The proposed method was applied to both synthetic models and field-scale examples located in Central Italy, where an accurate geophysical reconstruction is needed for the rehabilitation of existing dams. For all cases, joint inversion yielded superior results compared to independent inversion, demonstrating better agreement with available borehole data. The effectiveness of the joint approach was also demonstrated by the post-inversion tools, where the new cross-gradient index highlighted changes in structural similarity whilst fuzzy c-means clustering allowed for a quantitative reconstruction (position and shape) of the main units at the sites, facilitating the detection of site layering modifications.

Deep Electrical Resistivity Tomography for Detecting Gravitational Morpho-Structures in the Becca France Area (Aosta Valley, NW Italy)

Deep-seated gravitational slope deformations (DSGSDs) consist of gravity-induced, large-scale, gradual rock mass movements. In the Aosta Valley region (Valle d’Aosta NW Italy), DSGDs affect wide valley slopes and produce several interconnected morpho-structures that involve bedrock and Quaternary cover. Some DSGSD effects are not visible at the surface because of subglacial abrasion or burial by sediments and, therefore, are difficult to map with standard geomorphological surveys. This is the case for the Pointe Leysser DSGSD in the Aosta Valley, which is heavily influenced by the historical movements of the Verrogne-Clusellaz Glacier and its tributaries. We conducted a new geological investigation, integrated with deep electrical resistivity tomography geophysical surveys (ERTs). The ERT results were initially compared with geological/geomorphological evidence at the surface to define the correlation between the values and spatial distributions of electrical resistivity and the sediments, rocks, or morpho-structures. The resistivity values at various depths were subsequently analysed, interpreted, and discussed in conjunction with geological hypotheses. The geological and geophysical survey revealed three wide buried glacial valleys filled with glacial sediments and mapped the locations of gravitational morpho-structures at depth. These new data allowed us to draw a relationship between glacialism and gravitational evolution, distinguishing between pre-singlacial movements and postglacial movements.

Assessing the effect of offline topography on electrical resistivity measurements: insights from flood embankments

Summary Electrical resistivity tomography (ERT), a geophysical imaging method, is commonly used on flood embankments (dykes or levees) to characterise their internal structure and look for defects. These surveys often use a single line of electrodes to enable 2D imaging through the embankment crest, an approach that enables rapid and efficient surveying compared to 3D surveys. However, offline variations in topography can introduce artefacts into these 2D images, by affecting the measured resistivity data. Such topographic effects have only been explored on a site-specific basis. If the topographic effects can be assessed for a distribution of embankment geometries (e.g. slope angle and crest width) and resistivity variations, it would allow for targeted correction procedures and improved survey design. To investigate topographic effects on ERT measurements, we forward-modelled embankments with different trapezoidal cross-sections sat atop a flat foundation layer with contrasting resistivity values. Each was compared to a corresponding flat model with the same vertical resistivity distribution. The modelling workflow was designed to minimise the effect of forward modelling errors on the calculation of topographic effect. We ran 1872 unique embankment forward models, representing 144 geometries, each with 13 different resistivity contrasts. Modelling results show that offline topography affects the tested array types (Wenner-Schlumberger, Dipole-Dipole, and Multiple-Gradient) in slightly different ways, but the magnitudes are similar, so all are equally suitable for embankment surveys. Three separate mechanisms are found to cause topographic effects. The dominant mechanism is caused by the offline topography confining the electrical current flow, increasing the measured transfer resistance from the embankment model. The two other mechanisms, previously unidentified, decrease the measured transfer resistances from the embankment model compared to a layered half-space but only affect embankments with specific geometries and resistivity distributions. Overall, we found that for typical embankment geometries and resistivity distributions, the resistivity distribution has a greater control on the magnitude of the topographic effect than the exact embankment geometry: the subsurface resistivity distribution cannot be neglected. 2D inversions are suitable when both the embankment is more resistive than the foundations and when the embankment's cross-sectional area is greater than 4 m2/m2 (area scaled to an embankment with a height of 1 m). Topographic corrections, 3D data acquisition or 3D forward models are required when these conditions are not met. These are demonstrated using field data from an embankment at Hexham, Northumberland, UK. Improving the accuracy of the resistivity values in ERT models will enable more accurate ground models, better integration of resistivity data with geotechnical datasets, and will improve the translation of resistivity values into geotechnical properties. Such developments will contribute to a better characterised and safer flood defence network.