Improved characterisation and modelling of measurement errors in electrical resistivity tomography (ERT) surveys

Tso, Chak-Hau Michael; Kuras, O.; Wilkinson, Paul; Uhlemann, S.; Chambers, Jonathan; Meldrum, Philip; Graham, James; Sherlock, Emma F.; Binley, Andrew

doi:10.1016/j.jappgeo.2017.09.009

Cited by 73 publications

(59 citation statements)

References 63 publications

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“…The survey used 5 m spaced electrodes. The maximum spacing between current and potential dipoles was 50 m, given a depth of investigation of ~ 30 m. The survey included a full set of reciprocal measurements (e.g., Tso et al 2017) for data error analysis. Data quality was good (reciprocal errors typically less than 2%).…”

Section: Ertmentioning

confidence: 99%

Characterization of karst structures using quasi-3D electrical resistivity tomography

et al. 2019

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Karst is characteristically complex, hydrogeologically, due to a high degree of heterogeneity, which is often typified by specific features, for example, cavities and sinkholes, embedded in a landscape with significant spatial variability of weathering. Characterization of such heterogeneity is challenging with conventional hydrogeological methods, however, geophysical tools offer the potential to gain insight into key features that control the hydrological function of a karst aquifer. Electrical resistivity tomography (ERT) is recognized as the most effective technique for mapping karstic features. This method is typically carried out along transects to reveal 2D models of resistivity variability. However, karstic systems are rarely 2D in nature. In this study, ERT is employed in valley and hillslope regions of a karst critical zone observatory (Chenqi watershed, Guizhou province, China), using a quasi-3D approach. The results from the extensive geophysical surveys show that there is a strong association between resistivity anomalies and known karstic features. They highlight the significance of a marlstone layer in channeling spring flow in the catchment and confining deeper groundwater flow, evidenced by, for example, localized artesian conditions in observation wells. Our results highlight the need to analyze and interpret geophysical data in a threedimensional manner in such highly heterogeneous karstic environments, and the value of combining geological and hydrogeological data with geophysical models to help improve our understanding of the hydrological function of a karst system.

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Section: Ertmentioning

confidence: 99%

Characterization of karst structures using quasi-3D electrical resistivity tomography

et al. 2019

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“…Our initial model is a homogenous half-space with the average apparent resistivity value as starting value. We use the same strategy for the absolute and time-lapse inversions with the difference that for follow-on steps in the time-lapse we use the reference measurement (first data take at 14 October) as starting point for the difference inversion (note that we do not subtract absolute value images but run an inversion on the differences, see for details [ 30 , 31 , 32 , 33 , 34 ]. The set-up was maintained on the site for 67 days and in total 33 ERT measurements were carried out ( Figure 4 ).…”

Section: Methodsmentioning

confidence: 99%

Monitoring Soil Moisture Dynamics Using Electrical Resistivity Tomography under Homogeneous Field Conditions

Jong

Heijenk

Nijland

et al. 2020

Sensors

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There is a gap between lab experiments where resistivity–soil moisture relations are generally very good and field studies in complex environmental settings where relations are always less good and complicated by many factors. An experiment was designed where environmental settings are more controlled, the best outside laboratory, to assess the transferability from lab to outdoor. A field experiment was carried out to evaluate the use of electric resistivity tomography (ERT) for monitoring soil moisture dynamics over a period of 67 days. A homogeneous site in the central part of The Netherlands was selected consisting of grass pasture on an aeolian sand soil profile. ERT values were correlated to gravimetric soil moisture samples for five depths at three different dates. Correlations ranged from 0.43 to 0.73 and were best for a soil depth of 90 cm. Resistivity patterns over time (time-lapse ERT) were analyzed and related to rainfall events where rainfall infiltration patterns could be identified. Duplicate ERT measurements showed that the noise level of the instrument and measurements is low and generally below 3% for the soil profile below the mixed layer but above the groundwater. Although the majority of the measured resistivity patterns could be well explained, some artefacts and dynamics were more difficult to clarify, even so in this homogeneous field situation. The presence of an oak tree with its root structure and a ditch with surface water with higher conductivity may have an impact on the resistivity pattern in the soil profile and over time. We conclude that ERT allows for detailed spatial measurement of local soil moisture dynamics resulting from precipitation although field experiments do not yield accuracies similar to laboratory experiments. ERT approaches are suitable for detailed spatial analyses where probe or sample-based methods are limited in reach or repeatability.

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“…However, note that data uncertainty estimation in ERT is an ongoing topic of research; hence, a more sophisticated type of parameterization for data uncertainties may be developed in future. For instance, Tso et al () recently highlighted how ERT measurement errors may not be uncorrelated as is often assumed, and developed an error model that includes the effect of the combination of electrodes used for each measurement as well as the linear relationship between measurement error and transfer resistance (equation ). In addition, note that the term noise in this paper refers to both measurement and modeling errors; hence, the posterior uncertainty

σ_{k}^{post}

in equations encapsulates any effect by which the model cannot explain the observed data.…”

Section: Methodsmentioning

confidence: 99%

Transdimensional Electrical Resistivity Tomography

Galetti

Curtis

2018

JGR Solid Earth

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This paper shows that imaging the interior of solid bodies with fully nonlinear physics can be highly beneficial compared to imaging with the equivalent linearized tomographic methods and that this is true for a variety of different types of physics. Including full nonlinearity provides interpretable uncertainties and far greater depth of image penetration into unknown targets such as the Earth's subsurface. We use an adaptively parameterized Monte Carlo method to invert electrical resistivity data for the conductivity structure of the Earth and demonstrate the method on two field data sets. Key results include the observation of directly interpretable uncertainty loops which define possible geometrical variations in the edges of isolated anomalies, hence quantifying the spatial resolution of these boundaries. These topologies of uncertainties are similar to those observed when performing fully nonlinear seismic traveltime tomography. This shows that loop‐like uncertainty topologies are expected in the solutions to a wide variety of tomographic problems, using a variety of data types and hence laws of physics (here the Laplace equation; in previous work the Eikonal or ray equations). We also show that the depth to which we can construct a tomographic image using electrical data is extended by up to a factor of 8 using nonlinear methods compared to linearized inversion using common standard linearized programs. These advantages come at the cost of significantly increased computation. All of these results are illustrated on both synthetic and real data examples.

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Improved characterisation and modelling of measurement errors in electrical resistivity tomography (ERT) surveys

Cited by 73 publications

References 63 publications

Characterization of karst structures using quasi-3D electrical resistivity tomography

Characterization of karst structures using quasi-3D electrical resistivity tomography

Monitoring Soil Moisture Dynamics Using Electrical Resistivity Tomography under Homogeneous Field Conditions

Transdimensional Electrical Resistivity Tomography

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