Electrical Resistivity Tomography Monitoring Research Articles

Characterization of a Contaminated Site Using Hydro-Geophysical Methods: From Large-Scale ERT Surface Investigations to Detailed ERT and GPR Cross-Hole Monitoring

This work presents the results of an advanced geophysical characterization of a contaminated site, where a correct understanding of the dynamics in the unsaturated zone is fundamental to evaluate the effective management of the remediation strategies. Large-scale surface electrical resistivity tomography (ERT) was used to perform a preliminary assessment of the structure in a thick unsaturated zone and to detect the presence of a thin layer of clay supporting an overlying thin perched aquifer. Discontinuities in this clay layer have an enormous impact on the infiltration processes of both water and solutes, including contaminants. In the case here presented, the technical strategy is to interrupt the continuity of the clay layer upstream of the investigated site in order to prevent most of the subsurface water flow from reaching the contaminated area. Therefore, a deep trench was dug upstream of the site and, in order to evaluate the effectiveness of this approach in facilitating water infiltration into the underlying aquifer, a forced infiltration experiment was carried out and monitored using ERT and ground-penetrating radar (GPR) measurements in a cross-hole time-lapse configuration. The results of the forced infiltration experiment are presented here, with a particular emphasis on the contribution of hydro-geophysical methods to the general understanding of the subsurface water dynamics at this complex site.

Combined 2D- and 3D ERT monitoring as a geophysical tool for investigating spatial and temporal soil moisture fluctuations in a pine-beech forest

As climate change continues, forests are increasingly suffering from drought stress, which is leading to widespread forest dieback, but also to increased mortality of individual trees. In this regard, the impact of small-scale differences in water availability on individual trees has not yet been sufficiently studied to determine possible responses of different tree species to future droughts. Since conventional soil moisture monitoring and sampling methods only consider single points or small volumes, Electrical Resistivity Tomography (ERT) is becoming increasingly important to cover a larger survey area and to detect small-scale heterogeneities with regard to soil properties and soil moisture.The current study describes the application of a combined two- and three-dimensional geoelectrical monitoring approach with daily measurements over two years (May 2021 – April 2023) in a forest ecosystem in Lower Franconia (northwestern Bavaria, Germany), which is strongly affected by climate change. Soil water content, soil matric potential, throughfall, and stem flow are also measured at the forest site as well as precipitation at an adjacent forest clearing.The seasonally (long-term) and precipitation-driven (short-term) temporal change of soil resistivity is correlated strongly with the measured soil water content and matric potential. The applied 3D-ERT approach also allowed a first three-dimensional monitoring of the subsurface below a European beech located in the middle of the measuring grid with a daily resolution. The corresponding results also provide first indications that besides soil moisture changes also chemical processes in the subsurface may influence temporal resistivity changes in the soil of forest sites.The results of this study show that daily 3D-ERT is very suitable for investigating small-scale as well as short- and long-term variations in soil moisture, which is becoming increasingly important for understanding the causal relationships considering tree mortality and the subsurface.

Monitoring of Älvkarleby test embankment dam using 3D electrical resistivity tomography for detection of internal defects

Electrical resistivity tomography (ERT) is a potential-based method for detecting internal erosion in the core of embankment dams using the electrodes installed outside. This study aims at evaluating the practical capability of ERT monitoring for detecting internal defects in embankment dams. A test embankment dam with in-built well-defined defects was built in Älvkarleby, Sweden, to assess different monitoring systems including ERT and the defect locations were unknown to the monitoring teams. Between 7500 and 14,000 ERT data points were acquired daily, which were used to create the distribution of electrical resistivity models of the dam using 3D time-lapse inversion. The inversion models revealed a layered resistivity structure in the core that might be related to variations in water content or unintentional variations in material properties. Several anomalous zones that were not associated with the defects were detected, which might be caused by unintentional variations in material properties, temperature, water content, or other installations. The results located two out of five defects in the core, horizontal and vertical crushed rock zones, with a slight location shift for the horizontal zone. The concrete block defect in the core was indicated, although not as distinctly and with a lateral shift. The two remaining defects in the core, a crushed rock zone at the abutment and a wooden block and a crushed rock zone in the filter, were not discovered. The results cannot be used to fully evaluate the capability of ERT in detecting internal erosion under typical Swedish conditions due to limited seepage associated with the defects. Furthermore, scale effects need to be considered for larger dams.

Advancing Permafrost Monitoring With Autonomous Electrical Resistivity Tomography (A‐ERT): Low‐Cost Instrumentation and Open‐Source Data Processing Tool

AbstractPermafrost is a widespread phenomenon in the cold regions of the globe and is under‐represented in global monitoring networks. This study presents a novel low‐cost, low‐power, and robust Autonomous Electrical Resistivity Tomography (A‐ERT) monitoring system and open‐source processing tools for permafrost monitoring. The processing workflow incorporates diagnostic and filtering tools and utilizes open‐source software, ResIPy, for data inversion. The workflow facilitates quick and efficient extraction of key information from large data sets. Field experiments conducted in Antarctica demonstrated the system's capability to operate in harsh and remote environments and provided high‐temporal‐resolution imaging of ground freezing and thawing dynamics. This data set and processing workflow allow for a detailed investigation of how meteorological conditions impact subsurface processes. The A‐ERT setup can complement existing monitoring networks on permafrost and is suitable for continuous monitoring in polar and mountainous regions, contributing to cryosphere research and gaining deeper insights into permafrost and active layer dynamics.

Variations in Bedrock and Vegetation Cover Modulate Subsurface Water Flow Dynamics of a Mountainous Hillslope

AbstractPredicting the hydrological response of watersheds to climate disturbances requires a detailed understanding of the processes connecting hillslopes and streams. Using a network of soil moisture and temperature sensors, electrical resistivity tomography monitoring, and a weather station we assess the above and below‐ground processes driving the hydrological response of a hillslope during snowmelt and summer monsoon. The transect covers bedrock and vegetation gradients, with a steep upper part characterized by shallow bedrock, and gentle lower part underlain by colluvium. The main vegetation cover is conifers on the upper, and grass and veratrum on the lower part. Combined with a simplified hydrological model, we show that the thin soil layer of the steep slope acts as a preferential flow path, leading to mostly shallow lateral flow, interrupted by vertical flow, mostly at tree locations, and likely facilitated by flow along fractures and roots. Vertical flow and upstream‐driven groundwater dynamics are prevailing at the colluvium, presenting a very different hydrological behavior compared to the upper part. These results show that subsurface structure and features have a strong control on the hydrological response of a hillslope and that those can create considerably varying hydrological dynamics across small spatial scales.

Assessing the risk of slope failure to highway infrastructure using automated time-lapse electrical resistivity tomography monitoring

Electrical resistivity tomography (ERT) monitoring provides time-lapse images of the subsurface. These images can be used to assess spatiotemporal variation in moisture content, which is a key driver of slope failure, making ERT monitoring an effective tool to evaluate precursory conditions of failure. This work presents the results of ERT monitoring on a slope above a major highway located on the border between England and Wales. During highway construction in the 1960s the slope was subject to several large landslide events which resulted in the re-design of the carriageway and installation of engineered mitigation measures. A section of the slope known as the ‘partially slipped area’ exhibited partial displacement during this time but did not progress to full slope failure, and therefore presents an ongoing risk to the highway, even though it does not experience ongoing displacement. An ERT monitoring system was installed across this area to monitor subsurface variations in moisture content. The results show a complex pattern of subsurface moisture dynamics within the partially slipped area when compared to the adjacent area of stable slope. This is most likely a result of the uneven and hummocky terrain in the partially slipped area and its effects on rainfall infiltration, storage and drainage, combined with the displacement-induced jointing present in the underlying sandstone units. The ERT results are used to assess the volume of unstable ground, placing the volume at the upper end of estimates from previous studies. Furthermore, analysis of the ERT dataset for surface displacements shows no movement at the site, which is confirmed by analysis of differential LiDAR plots and ground motion data derived from InSAR. This study demonstrates the application of ERT monitoring on a low activity, high risk slope, highlighting the need to understand subsurface processes at the slope-scale to inform long-term slope management.

Electrical Resistivity Tomography (ERT) Monitoring of Groundwater Flow Condition Surround Deep Excavation in Slope Area

Indonesia is a country with lots of mountain and hills, conducting deep excavation around slope areas will affect the groundwater. Deep excavation will change the groundwater table and hydrogeological condition. In order to monitoring the groundwater flow from the deep excavation in slope area, Electrical Resistivity Tomography used to monitoring the area surround the deep excavation project. The resistivity distribution in the area can be determined by knowing the condition of the soil around the deep excavation project through ERT (Electrical Resistivity Tomography). By utilizing passive ERT, vital parameters, such as porosity and volumetric water content, can be estimated, enabling the calculation of water saturation maps from inverted resistivity values. The resistivity conditions of the soil are continuously monitored, leading to the identification of patterns in soil resistivity movement, and the detection of potential instabilities at the boundaries between areas with varying water saturation levels.

Мониторинговые электротомографические исследования зоны Иссык-Атинского разлома (Северный Тянь-Шань)

In 2023, monitoring geophysical studies were carried out using the electrical resistivity tomography (ERT) method along three profiles that cross the strike zone of the Issyk-Ata fault in the transverse direction. A detailed study was carried out of the observed variations in apparent electrical resistivity, which characterize the change in the electrical properties of the upper part of the Earth's crust section with a 40-minute discretization in time. Using the analysis of difference pseudo-sections of apparent resistivity, constructed based on the results of ERT monitoring, the most informative pseudo-depth interval from the point of view of geoelectric activity was determined for all three monitoring profiles. Accordingly, for a pseudo-depth of 24 m on each monitoring profile, an assessment was made of the geodynamic activity of these sections of the Issyk-Ata fault based on an analysis of the magnitude of two parameters: the amplitude of apparent resistivity variations and the correlation coefficient of electrical resistivity variations with lunar-solar solid tides. High values of these parameters, in our opinion, determine the location of modern active fault zones.

Brief communication: Mountain permafrost acts as an aquitard during an infiltration experiment monitored with electrical resistivity tomography time-lapse measurements

Abstract. Frozen layers within the subsurface of rock glaciers are generally assumed to act as aquicludes or aquitards. So far, this behavior has been mainly defined by analyzing the geochemical characteristics of spring waters. In this work, for the first time, we experimentally confirmed this assumption by executing an infiltration test in a rock glacier of the Southern Alps, Italy. Time-lapse electrical resistivity tomography (ERT) technique monitored the infiltration of 800 L of saltwater released on the surface of the rock glacier; 24 h ERT monitoring highlighted that the injected water was not able to infiltrate into the underlying frozen layer.

Monitoring spatiotemporal soil moisture variability in the unsaturated zone of a mixed forest using electrical resistivity tomography

AbstractEuropean forests are suffering considerably from the consequences of the droughts of recent years, and the exact reasons and influencing factors for this are still not fully understood. This study was conducted to characterize the changes and dynamics of soil moisture in a mixed forest in northern Bavaria within 1 year. Since electrical resistivity correlates well with soil water content, we used two‐dimensional electrical resistivity tomography (ERT) monitoring and time‐lapse analyses to supplement punctual measurements by sensors and soil analyses to show soil moisture changes throughout a whole year (2020–2021). While the topsoil dries out significantly from summer to autumn down to a depth of about 3 m, a clear increase in soil water content and a decrease in resistivity below 3 m can be observed during winter period. Anomalies in the topsoil (0–1 m) showing lower resistivities than the surrounding substrate could be related to tree positions by additional terrestrial laser scans. A significant relationship could be found between tree crown projection area and resistivity in 1–2 m depth. We found a trend that mean resistivity below pine is lower as below beech. ERT data were also used to estimate the soil water content via Archie's law and the results correlate strongly with the measured values, but the degree of correlation varies depending on the depth level. ERT as a noninvasive method, in combination with additional data, for example, on the vitality status of individual trees, could help to better understand root water uptake and water supply to trees, especially during periods of drought.

Evaluation of submarine groundwater discharge and associated beach groundwater dynamics

ABSTRACT This paper reports the dynamism of a submarine groundwater discharge (SGD) zone in SW India. Two electrical resistivity tomography (ERT) surveys were conducted in the project area to delineate the seawater-fresh water interface and characterize the subsurface aquifer layers. Beach groundwater dynamics were also studied by continuously monitoring salinity, temperature, and nutrient concentration in the groundwater from three shallow dug wells on the beach. The ERT surveys were planned in such a way as to fall between these dug wells. The flow domain was modeled using a numerical modeling approach, and the rate of fresh SGD flux and its spatial variation along the coastline has been estimated. The study proves that the numerical modeling approach combined with other field measurements and observations, such as ERT and continuous monitoring gives a comprehensive understanding of SGD and associated processes.

Hydro-mechanical behaviour of a cement–bentonite mixture along evaporation and water-uptake controlled paths

The results of a laboratory investigation on the effects of drying and wetting on the hydro-mechanical behaviour of a cement–bentonite mixture are presented. A large hysteresis along the hydraulic paths was found for what concerns both the water retention and the volume strains. This might be related to the shrinkage of cement bentonite clusters and to the development of micro-cracks, that were observed with a microscope along drying. Macroscopic cracks developed in a squat sample which had been cured for 28 days and was then left to dry in the laboratory environment, while this did not occur in an analogous sample cured for 60 days, possibly in virtue of its higher strength as detected through a pocket penetrometer. Water uptake after partial desaturation of squat and column samples took place in short times with respect to drying, but it did not allow for a full recovery of the initial water content. Electrical Resistivity Tomography (ERT) monitoring provided reliable water content determinations in the high range and correct indication of crack patterns at low water contents. A good reproduction of the experimental results was obtained with a coupled Thermo-Hydraulic model formulated on purpose.

Long-term geoelectrical monitoring of landslides in natural and engineered slopes

Developments in time-lapse electrical resistivity tomography (ERT) technology are transforming our ability to monitor the subsurface due to purpose-built monitoring instruments, advances in automation and modeling, and the resulting improvements in spatial and temporal resolution. We describe the development of a novel ERT-based remote monitoring system called PRIME that integrates new low-power measurement instrumentation with data delivery, automated data processing and image generation, and web-based information delivery. Due to the sensitivity of ERT to hydrologic processes in the near surface, we focus on the application of PRIME for moisture-driven landslide monitoring. Case examples are considered of landslides in engineered and natural slopes, including those impacting geotechnical assets in rail and highways, where slope hydrology is seen to be controlled by lithology, vegetation, fissuring, and drainage structures. We conclude by taking a forward look at emerging developments in ERT monitoring relating to hardware, software and modeling, and applications.

Electrical resistivity tomography (ERT) monitoring of leachate seepage from an animal carcass waste (ACW) facility, South Korea

The South Korean government culled and buried numerous pigs to contain the 2011 outbreak of foot-and-mouth disease. Pollutants were detected in groundwater samples collected from an observation well near animal carcass waste (ACW) facilities used to dispose of some of the culled animals. Pollutants appeared to be leachate seeping through damaged shields installed in the ACW facilities prior to burial of the carcasses. Because electric conductivity of leachate is relatively low compared to fresh groundwater, we assumed that electrical resistivity tomography (ERT) is effective to investigate the spatial distribution of the conductive materials. This research demonstrated the use of 3D ERT monitoring to characterize spatial and temporal changes of the leachate. Low-resistivity anomalies <23 Ωm were distributed adjacent to the ACW facilities in time-lapse ERT images. Although the size of the initial low-resistivity anomalies was the largest the time-lapse ERT images, the average resistivities were gradually reduced. We also identified that the resistivities of the low-resistivity anomalies gradually increased, whereas the resistivities decreased away from the ACW facilities using resistivity ratio maps. It was considered that these temporal and spatial changes were related to dilution of the leachate with rainwater and the leachate migration along the northwest slope. We therefore believed that the 3D ERT monitoring could be a useful tool for detecting both the distribution and migration of the leachate.

Quantifying Reagent Spreading by Cross‐Borehole Electrical Tomography to Assess Performance of Groundwater Remediation

AbstractIn situ remediation of contaminated groundwater often relies on the installation of a treatment zone (TZ) degrading the contamination. Zero‐valent‐iron (ZVI) is a type of reagent used for this purpose. Adequate delivery of ZVI in the whole target volume is particularly challenging and requires monitoring with high spatial resolution. We present a monitoring tool for imaging the dynamic spreading of ZVI and its associated ionic cloud, using cross‐borehole time‐lapse electrical resistivity tomography (ERT). This tool works in urban areas and is particularly suitable for achieving the required spatial resolution at the scale of the target volume. Groundwater and sediment samples show a consistent spatial and temporal distribution of the remediation cloud with cross‐borehole ERT. Yet, the 2D anomalies observed with cross‐borehole ERT provide a more spatially complete and rapid image of the remediation cloud distribution than if based solely on monitoring screens. At the study site, ZVI injection leads to uneven spreading, clearly documented by cross‐borehole ERT monitoring. The benefit of hydraulic conductivity (K) mapping by cross‐borehole induced polarization (IP) to understand unexpected injection paths (upstream leakage, spreading in preferred pathways) is investigated. A 2D, IP‐based, continuous, and coherent K‐distribution is obtained that compares well with estimations by grain size analyses from the TZ. However, the IP‐based K‐field fails at predicting injection paths, suggesting the creation of pathways during the high‐pressure injection of ZVI. Cross‐borehole time‐lapse ERT is the most promising geophysical tool for performance assessment of in situ remediation involving reagents with conductivity contrast.

Using Electrical Resistivity Tomography to Monitor the Evolution of Landslides’ Safety Factors under Rainfall: A Feasibility Study Based on Numerical Simulation

Although electrical resistivity tomography (ERT) may gather the internal resistivity information from a landslide area in a large-scale, low-cost, and non-invasive manner compared to point-based sensor monitoring technology, the indirect resistivity information obtained cannot directly evaluate the landslide’s current mechanical status, such as stress, strength, etc. Based on ERT monitoring data, a framework for quantitatively and directly evaluating the evolution of the factor of safety (FOS) of landslides during rainfall is proposed. The framework first inverts ERT observation data using the inexact Gauss–Newton method based on multiple constraints to obtain a more realistic resistivity distribution, then calculates the saturation distribution using Archie’s equation, and finally calculates the FOS of landslides using the finite element strength reduction method. Twelve sets of numerical experiments were designed and carried out based on the synthetic data of a theoretical model. The experimental results show that the proposed framework is valid and reliable under various arrays, apparent resistivity noise, and uncertainty in the water-electric correlation curve, with the Dipole-Dipole array outperforming the others in terms of accuracy, sensitivity, and anti-noise capability. The proposed framework is significant in improving ERT monitoring and early warning capabilities for rainfall-induced landslides.

4D electrical resistivity tomography for assessing the influence of vegetation and subsurface moisture on railway cutting condition

Instability of slopes, embankments, and cuttings on the railway network is increasingly prevalent globally. Monitoring vulnerable infrastructure aids in geotechnical asset management, and improvements to transport safety and efficiency. Here, we examine the use of a novel, near-real-time Electrical Resistivity Tomography (ERT) monitoring system for assessing the stability of a railway cutting in Leicestershire, United Kingdom. In 2015, an ERT monitoring system was installed across a relict landslide (grassed) and an area of more stable ground on either side (wooded), to monitor changes in electrical resistivity through time and space, and to assess the influence of different types of vegetation on the stability of transportation infrastructure. Two years of 4-Dimensional ERT monitoring results are presented here, and petrophysical relationships developed in the laboratory are applied to calibrate the resistivity models in order to provide an insight into hydrogeological pathways within a railway cutting. The influence of vegetation type on subsurface moisture pathways and on slope stability is also assessed – here we find that seasonal subsurface changes in moisture content and soil suction are exacerbated by the presence of trees (wooded area). This results in shrink-swell behaviour of the clays comprising the railway cutting, resulting in fissuring and a reduction in shear strength, leading to instability. As such, it is proposed that on slopes comprised of expansive soils, grassed slopes are beneficial for stability. Insights into the use of 4-D ERT for monitoring railway infrastructure gained from this study may be applied to the monitoring of critical geotechnical assets elsewhere.

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R2-score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(104) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(105) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈O(105)−O(107) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

Monitoring critically saturated conditions for shallow landslide occurrence using electrical resistivity tomography

AbstractSoil wetness is an important property in determining the variable disposition of hillslopes to shallow landslides. Recent studies have demonstrated the potential of in situ soil wetness information for landslide early warning. However, the spatial representativeness of in situ sensors may be affected by local heterogeneities of soil properties and hydrological processes, and their installation may be destructive. Electrical resistivity tomography (ERT) has been used in the past to estimate plot‐scale soil moisture variation and may overcome these limitations. In this study, we installed and operated an automated ERT monitoring system on a landslide‐prone hillslope in the Napf region (Switzerland). The system was operational during a period of 9 mo, and measurements were conducted at high temporal resolution and under different soil hydrological conditions. Electrical resistivity was measured along two perpendicular profile lines in Wenner–Schlumberger configuration at 0.25‐m electrode spacing. Soil saturation was calculated by the Archie's law and the parameters were fitted with colocated soil moisture sensors. Comparison of ERT‐derived soil moisture with soil wetness from in situ sensors showed a good correlation, and infiltration properties critical for landslide early warning could be reliably reproduced. Further, analysis of spatial saturation variation revealed that ERT was capable to detect heterogeneities of soil hydrological process. Under highly saturated conditions, the reliability of the saturation estimation was affected by an increased number of faulty measurements and the spatial heterogeneity of the infiltration process.

Large-Scale Physical Modeling of Salt-Water Intrusion

Salt-water intrusion (SWI) is a worldwide problem increasingly affecting coastal aquifers, exacerbated by climate changes and growing demand of fresh-water. Therefore, research on this topic using both physical and numerical modeling has been intensified, aiming to achieve better predictions of the salt-water wedge evolution and to design suitable countermeasures to its negative effects. This work presents a laboratory facility designed to conduct SWI experiments that can be used as benchmarks for numerical models. To this end, the laboratory facility has been designed to limit errors and provide redundant measurements of hydraulic heads and discharged flow rates. Moreover, the size of the facility allows us to monitor the salt-water wedge evolution by a specifically designed electrical resistivity tomography (ERT) monitoring system. To demonstrate the capabilities of the laboratory facility, we carried out a simple 36-h long SWI experiment in a homogeneous porous medium: during the initial 24 h the salt-water wedge evolved without any external forcing, while in the last 12 h, fresh-water was pumped out to simulate aquifer exploitation. The experiment was monitored through ERT and photos of the salt-water wedge collected at regular time intervals. The SUTRA code was used to reproduce the experimental results, by calibrating only the dispersivities. The ERT results show a good correlation with simulated concentrations between the borehole electrodes, the most sensitive zone of the monitored area, demonstrating that ERT can be used for laboratory evaluations of the salt-water evolution. Overall, the agreement between observed data, numerical simulations, and ERT results demonstrates that the proposed laboratory facility can provide valuable benchmarks for future studies of SWI, even in more complex settings.