A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models

Arboleda‐Zapata, Mauricio; Guillemoteau, Julien; Tronicke, Jens

doi:10.1016/j.jappgeo.2021.104512

Cited by 5 publications

(7 citation statements)

References 38 publications

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“…However, to confirm and validate this interpretation, complementary geophysical surveys such as seismic refraction (e.g., Juhojuntti & Kamm, 2015) or borehole‐based explorations are needed. Furthermore, using layer‐based parameterisation approaches to invert the geophysical data (e.g., Arboleda‐Zapata, Angelopoulos et al., 2022; Arboleda‐Zapata, Guillemoteau et al., 2022) might be helpful to resolve the bedrock structure. Overlying this inferred bedrock, all ERT profiles show a relatively low conductive layer with a thickness of up to 5 m, which may represent coarse gravel lag deposits.…”

Section: Discussionmentioning

confidence: 99%

Tracing past extreme floods on an alluvial fan using geophysical surveying

Arboleda‐Zapata,

Guillemoteau,

Lucía

et al. 2023

Earth Surf Processes Landf

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SummarySedimentary units in alluvial fans may record gradual transport and deposition during multiple floods or sediment‐laden flows or, conversely, during few catastrophic events. While outcrops are a valuable source of direct information to constrain past geomorphic and hydrologic processes, such exposures are scarce, especially along aggrading rivers or those that have been subject to recent catastrophic sedimentation. In this context, near‐surface geophysical techniques can constrain the dimensions, internal architecture, composition, and petrophysical properties of different sedimentary units. We consider the Grimmbach alluvial fan in the cuesta landscape of southwestern Germany, which was heavily impacted by sediment and wood loads during a flash flood in 2016; published radiocarbon dates indicate that at least three floods similar to the one in 2016 may have occurred since the 17th century. To test whether and to which detail near‐surface geophysics might reveal the sedimentary legacy of these floods, we survey the Grimmbach alluvial fan using detailed topographic data and geophysical imaging based on electromagnetic induction, electrical resistivity tomography (ERT), and ground‐penetrating radar. Our geophysical results indicate former channel courses and two coarse bar deposits up to 3 m below the surface, which are comparable with the more extensive bar deposits of the 2016 flood. From the ERT models, we interpret coarse, up to 5 m thick, gravel lag overlying bedrock at a maximum depth of 10 m. Our geophysical results also highlight patches of finer materials derived from gradual sedimentation and soil development. Overall, our results show that the Grimmbach alluvial fan may have formed and reshaped during catastrophic flows, which likely caused channel avulsions. Our findings point to the need to reconsider flash flood and debris‐flow hazards in similar headwaters and fans of this seemingly quiescent cuesta landscape in southern Germany.

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Section: Discussionmentioning

confidence: 99%

Tracing past extreme floods on an alluvial fan using geophysical surveying

Arboleda‐Zapata,

Guillemoteau,

Lucía

et al. 2023

Earth Surf Processes Landf

Self Cite

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“…Because we expect some of these processes and structures at our field sites, we adopt a strategy based on the sums of arctangent functions because it allows for abrupt and smooth changes along the interfaces (e.g., Roy et al, 2005;Rumpf and Tronicke, 2015). Following Arboleda-Zapata et al (2022), the sums of arctangent functions for a single interface can be written as…”

Section: Two-dimensional Layer-based Model Parameterizationmentioning

confidence: 99%

“…To ensure good mesh quality, we constrain the minimum angle within each cell to 33.5 • (Shewchuk, 1996). This parameterization strategy allows us to calculate the forward response with high precision and with a reasonable amount of time (Arboleda-Zapata et al, 2022). At the end, when the optimization reaches the maximum number of iterations or a minimum threshold in the objective function, we save the final best model.…”

Section: Inversion Strategymentioning

confidence: 99%

“…Additionally, one may also consider different gradient-based image-processing approaches to extract interfaces from the inverted resistivity model (e.g., Hsu et al, 2010;Chambers et al, 2012). Finally, when we have ample evidence of a sharp contact between the unfrozen and frozen sediments (e.g., Overduin et al, 2015b;Angelopoulos et al, 2020a), a layer-based model parameterization combined with a local and/or global inversion algorithms might be more suitable (e.g., Auken and Christiansen, 2004;Akça and Basokur, 2010;De Pasquale et al, 2019;Arboleda-Zapata et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…In this study, we adapt the inversion and ensemble interpretation strategies as proposed by Arboleda-Zapata et al (2022) to study submarine permafrost environments of the Arctic in terms of the resistivity distribution of the unfrozen and frozen sediments and the position of the IBPT, including estimates of uncertainties. We analyze and compare ERT data collected at two field sites in the Arctic characterized by different environmental conditions regarding seawater depth and resistivity, coastal erosion rate, and the sediment porewater chemistry.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the capabilities of electrical resistivity tomography to study subsea permafrost

et al. 2022

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Abstract. Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.

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Inversion géostatistique par itérations de la tomographie de résistivité électrique

Pereira,

Gómez-Hernández,

Zanini

et al. 2023

Hydrogeol J

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Electrical resistivity tomography (ERT) is a geophysical method used to create an image of the subsurface due to its sensitivity to porosity, water saturation, and pore fluid salinity. This geophysical method has been widely applied in the investigation of mineral and groundwater resources, as well as in archaeological, environmental, and engineering studies. The prediction of subsurface properties, such as electrical conductivity, from measured ERT data requires solving a challenging geophysical inversion problem. This work proposes an iterative geostatistical resistivity inversion method using stochastic sequential simulation and co-simulation as stochastic model perturbation and update techniques. Electrical resistivity models are generated conditioned to a target histogram, often retrieved from available resistivity borehole data, and assuming a spatial continuity pattern described by a variogram model. From the electrical resistivity models, a finite-volume approximation of Poisson’s equation is used to compute synthetic ERT data. The misfit between predicted and observed data drives the convergence of an iterative procedure and conditions the co-simulation of new models in the subsequent iterations. This methodology is applied to a two-dimensional synthetic case, and a set of two-dimensional profiles obtained from an ERT survey carried out in southern Portugal. In both application examples, the final models predict ERT data that match the observed ones while reproducing borehole data and imposed variogram models. The results obtained in both data sets are compared against a commercial deterministic ERT inversion methodology, showing the ability of the proposed method to model small-scale variability and assess spatial uncertainty.

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A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models

Cited by 5 publications

References 38 publications

Tracing past extreme floods on an alluvial fan using geophysical surveying

Tracing past extreme floods on an alluvial fan using geophysical surveying

Exploring the capabilities of electrical resistivity tomography to study subsea permafrost

Inversion géostatistique par itérations de la tomographie de résistivité électrique

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