@article{KloseGuillemoteauVignolietal.2023, author = {Klose, Tim and Guillemoteau, Julien and Vignoli, Giulio and Walter, Judith and Herrmann, Andreas and Tronicke, Jens}, title = {Structurally constrained inversion by means of a Minimum Gradient Support regularizer: examples of FD-EMI data inversion constrained by GPR reflection data}, series = {Geophysical journal international}, volume = {233}, journal = {Geophysical journal international}, number = {3}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0956-540X}, doi = {10.1093/gji/ggad041}, pages = {1938 -- 1949}, year = {2023}, abstract = {Many geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a prioriinformation is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally constrained smooth inversion as well as to more standard (i.e., not structurally constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.}, language = {en} } @misc{ArboledaZapataAngelopoulosOverduinetal.2022, author = {Arboleda-Zapata, Mauricio and Angelopoulos, Michael and Overduin, Pier Paul and Grosse, Guido and Jones, Benjamin M. and Tronicke, Jens}, title = {Exploring the capabilities of electrical resistivity tomography to study subsea permafrost}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1285}, issn = {1866-8372}, doi = {10.25932/publishup-57123}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-571234}, pages = {4423 -- 4445}, year = {2022}, 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.}, language = {en} } @article{ArboledaZapataGuillemoteauTronicke2022, author = {Arboleda-Zapata, Mauricio and Guillemoteau, Julien and Tronicke, Jens}, title = {A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models}, series = {Journal of applied geophysics}, volume = {196}, journal = {Journal of applied geophysics}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0926-9851}, doi = {10.1016/j.jappgeo.2021.104512}, pages = {12}, year = {2022}, abstract = {Electrical resistivity tomography (ERT) aims at imaging the subsurface resistivity distribution and provides valuable information for different geological, engineering, and hydrological applications. To obtain a subsurface resistivity model from measured apparent resistivities, stochastic or deterministic inversion procedures may be employed. Typically, the inversion of ERT data results in non-unique solutions; i.e., an ensemble of different models explains the measured data equally well. In this study, we perform inference analysis of model ensembles generated using a well-established global inversion approach to assess uncertainties related to the nonuniqueness of the inverse problem. Our interpretation strategy starts by establishing model selection criteria based on different statistical descriptors calculated from the data residuals. Then, we perform cluster analysis considering the inverted resistivity models and the corresponding data residuals. Finally, we evaluate model uncertainties and residual distributions for each cluster. To illustrate the potential of our approach, we use a particle swarm optimization (PSO) algorithm to obtain an ensemble of 2D layer-based resistivity models from a synthetic data example and a field data set collected in Loon-Plage, France. Our strategy performs well for both synthetic and field data and allows us to extract different plausible model scenarios with their associated uncertainties and data residual distributions. Although we demonstrate our workflow using 2D ERT data and a PSObased inversion approach, the proposed strategy is general and can be adapted to analyze model ensembles generated from other kinds of geophysical data and using different global inversion approaches.}, language = {en} } @article{ArboledaZapataAngelopoulosOverduinetal.2022, author = {Arboleda-Zapata, Mauricio and Angelopoulos, Michael and Overduin, Pier Paul and Grosse, Guido and Jones, Benjamin M. and Tronicke, Jens}, title = {Exploring the capabilities of electrical resistivity tomography to study subsea permafrost}, series = {The Cryosphere}, volume = {16}, journal = {The Cryosphere}, publisher = {Copernicus}, address = {Katlenburg-Lindau}, issn = {1994-0424}, doi = {10.5194/tc-16-4423-2022}, pages = {4423 -- 4445}, year = {2022}, 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.}, language = {en} } @article{KloseGuillemoteauVignolietal.2022, author = {Klose, Tim and Guillemoteau, Julien and Vignoli, Giulio and Tronicke, Jens}, title = {Laterally constrained inversion (LCI) of multi-configuration EMI data with tunable sharpness}, series = {Journal of applied geophysics}, volume = {196}, journal = {Journal of applied geophysics}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0926-9851}, doi = {10.1016/j.jappgeo.2021.104519}, pages = {9}, year = {2022}, abstract = {Frequency-domain electromagnetic (FDEM) data are commonly inverted to characterize subsurface geoelectrical properties using smoothness constraints in 1D inversion schemes assuming a layered medium. Smoothness constraints are suitable for imaging gradual transitions of subsurface geoelectrical properties caused, for example, by varying sand, clay, or fluid content. However, such inversion approaches are limited in characterizing sharp interfaces. Alternative regularizations based on the minimum gradient support (MGS) stabilizers can, instead, be used to promote results with different levels of smoothness/sharpness selected by simply acting on the so-called focusing parameter. The MGS regularization has been implemented for different kinds of geophysical data inversion strategies. However, concerning FDEM data, the MGS regularization has only been implemented for vertically constrained inversion (VCI) approaches but not for laterally constrained inversion (LCI) approaches. We present a novel LCI approach for FDEM data using the MGS regularization for the vertical and lateral direction. Using synthetic and field data examples, we demonstrate that our approach can efficiently and automatically provide a set of model solutions characterized by different levels of sharpness and variable lateral consistencies. In terms of data misfit, the obtained set of solutions contains equivalent models allowing us also to investigate the non-uniqueness of FDEM data inversion.}, language = {en} } @article{KoyanTronickeAllroggen2021, author = {Koyan, Philipp and Tronicke, Jens and Allroggen, Niklas}, title = {3D ground-penetrating radar attributes to generate classified facies models}, series = {Geophysics}, volume = {86}, journal = {Geophysics}, number = {6}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2021-0204.1}, pages = {B335 -- B347}, year = {2021}, abstract = {Ground-penetrating radar (GPR) is a standard geophysical technique used to image near-surface structures in sedimentary environments. In such environments, GPR data acquisition and processing are increasingly following 3D strategies. However, the processed GPR data volumes are typically still interpreted using selected 2D slices and manual concepts such as GPR facies analyses. In seismic volume interpretation, the application of (semi-)automated and reproducible approaches such as 3D attribute analyses as well as the production of attribute-based facies models are common practices today. In contrast, the field of 3D GPR attribute analyses and corresponding facies models is largely untapped. We have developed and applied a workflow to produce 3D attribute-based GPR facies models comprising the dominant sedimentary reflection patterns in a GPR volume, which images complex sandy structures on the dune island of Spiekeroog (Northern Germany). After presenting our field site and details regarding our data acquisition and processing, we calculate and filter 3D texture attributes to generate a database comprising the dominant texture features of our GPR data. Then, we perform a dimensionality reduction of this database to obtain meta texture attributes, which we analyze and integrate using composite imaging and (also considering additional geometric information) fuzzy c-means cluster analysis resulting in a classified GPR facies model. Considering our facies model and a corresponding GPR facies chart, we interpret our GPR data set in terms of near-surface sedimentary units, the corresponding depositional environments, and the recent formation history at our field site. Thus, we demonstrate the potential of our workflow, which represents a novel and clear strategy to perform a more objective and consistent interpretation of 3D GPR data collected across different sedimentary environments.}, language = {en} } @article{AngelopoulosOverduinWestermannetal.2020, author = {Angelopoulos, Michael and Overduin, Pier Paul and Westermann, Sebastian and Tronicke, Jens and Strauss, Jens and Schirrmeister, Lutz and Biskaborn, Boris and Liebner, Susanne and Maksimov, Georgii and Grigoriev, Mikhail N. and Grosse, Guido}, title = {Thermokarst lake to lagoon transitions in Eastern Siberia}, series = {Journal of geophysical research : Earth surface}, volume = {125}, journal = {Journal of geophysical research : Earth surface}, number = {10}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1029/2019JF005424}, pages = {21}, year = {2020}, abstract = {As the Arctic coast erodes, it drains thermokarst lakes, transforming them into lagoons, and, eventually, integrates them into subsea permafrost. Lagoons represent the first stage of a thermokarst lake transition to a marine setting and possibly more saline and colder upper boundary conditions. In this research, borehole data, electrical resistivity surveying, and modeling of heat and salt diffusion were carried out at Polar Fox Lagoon on the Bykovsky Peninsula, Siberia. Polar Fox Lagoon is a seasonally isolated water body connected to Tiksi Bay through a channel, leading to hypersaline waters under the ice cover. The boreholes in the center of the lagoon revealed floating ice and a saline cryotic bed underlain by a saline cryotic talik, a thin ice-bearing permafrost layer, and unfrozen ground. The bathymetry showed that most of the lagoon had bedfast ice in spring. In bedfast ice areas, the electrical resistivity profiles suggested that an unfrozen saline layer was underlain by a thick layer of refrozen talik. The modeling showed that thermokarst lake taliks can refreeze when submerged in saltwater with mean annual bottom water temperatures below or slightly above 0 degrees C. This occurs, because the top-down chemical degradation of newly formed ice-bearing permafrost is slower than the refreezing of the talik. Hence, lagoons may precondition taliks with a layer of ice-bearing permafrost before encroachment by the sea, and this frozen layer may act as a cap on gas migration out of the underlying talik.}, language = {en} } @article{KoyanTronicke2020, author = {Koyan, Philipp and Tronicke, Jens}, title = {3D modeling of ground-penetrating radar data across a realistic sedimentary model}, series = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, volume = {137}, journal = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0098-3004}, doi = {10.1016/j.cageo.2020.104422}, pages = {9}, year = {2020}, abstract = {Ground-penetrating radar (GPR) is an established geophysical tool to explore a wide range of near-surface environments. Today, the use of synthetic GPR data is largely limited to 2D because 3D modeling is computationally more expensive. In fact, only recent developments of modeling tools and powerful hardware allow for a time-efficient computation of extensive 3D data sets. Thus, 3D subsurface models and resulting GPR data sets, which are of great interest to develop and evaluate novel approaches in data analysis and interpretation, have not been made publicly available up to now.
We use a published hydrofacies data set of an aquifer-analog study within fluvio-glacial deposits to infer a realistic 3D porosity model showing heterogeneities at multiple spatial scales. Assuming fresh-water saturated sediments, we generate synthetic 3D GPR data across this model using novel GPU-acceleration included in the open-source software gprMax. We present a numerical approach to examine 3D wave-propagation effects in modeled GPR data. Using the results of this examination study, we conduct a spatial model decomposition to enable a computationally efficient 3D simulation of a typical GPR reflection data set across the entire model surface. We process the resulting GPR data set using a standard 3D structural imaging sequence and compare the results to selected input data to demonstrate the feasibility and potential of the presented modeling studies. We conclude on conceivable applications of our 3D GPR reflection data set and the underlying porosity model, which are both publicly available and, thus, can support future methodological developments in GPR and other near-surface geophysical techniques.}, language = {en} } @article{TronickeAllroggenBiermannetal.2020, author = {Tronicke, Jens and Allroggen, Niklas and Biermann, Felix and Fanselow, Florian and Guillemoteau, Julien and Krauskopf, Christof and L{\"u}ck, Erika}, title = {Rapid multiscale analysis of near-surface geophysical anomaly maps}, series = {Geophysics}, volume = {85}, journal = {Geophysics}, number = {4}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa, Okla.}, issn = {0016-8033}, doi = {10.1190/GEO2019-0564.1}, pages = {B109 -- B118}, year = {2020}, abstract = {In near- surface geophysics, ground-based mapping surveys are routinely used in a variety of applications including those from archaeology, civil engineering, hydrology, and soil science. The resulting geophysical anomaly maps of, for example, magnetic or electrical parameters are usually interpreted to laterally delineate subsurface structures such as those related to the remains of past human activities, subsurface utilities and other installations, hydrological properties, or different soil types. To ease the interpretation of such data sets, we have developed a multiscale processing, analysis, and visualization strategy. Our approach relies on a discrete redundant wavelet transform (RWT) implemented using cubic-spline filters and the a trous algorithm, which allows to efficiently compute a multiscale decomposition of 2D data using a series of 1D convolutions. The basic idea of the approach is presented using a synthetic test image, whereas our archaeogeophysical case study from northeast Germany demonstrates its potential to analyze and process rather typical geophysical anomaly maps including magnetic and topographic data. Our vertical-gradient magnetic data show amplitude variations over several orders of magnitude, complex anomaly patterns at various spatial scales, and typical noise patterns, whereas our topographic data show a distinct hill structure superimposed by a microtopographic stripe pattern and random noise. Our results demonstrate that the RWT approach is capable to successfully separate these components and that selected wavelet planes can be scaled and combined so that the reconstructed images allow for a detailed, multiscale structural interpretation also using integrated visualizations of magnetic and topographic data. Because our analysis approach is straightforward to implement without laborious parameter testing and tuning, computationally efficient, and easily adaptable to other geophysical data sets, we believe that it can help to rapidly analyze and interpret different geophysical mapping data collected to address a variety of near-surface applications from engineering practice and research.}, language = {en} } @article{AllroggenBeiterTronicke2020, author = {Allroggen, Niklas and Beiter, Daniel and Tronicke, Jens}, title = {Ground-penetrating radar monitoring of fast subsurface processes}, series = {Geophysics}, volume = {85}, journal = {Geophysics}, number = {3}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2019-0737.1}, pages = {A19 -- A23}, year = {2020}, abstract = {Earth and environmental sciences rely on detailed information about subsurface processes. Whereas geophysical techniques typically provide highly resolved spatial images, monitoring subsurface processes is often associated with enormous effort and, therefore, is usually limited to point information in time or space. Thus, the development of spatial and temporal continuous field monitoring methods is a major challenge for the understanding of subsurface processes. We have developed a novel method for ground-penetrating-radar (GPR) reflection monitoring of subsurface flow processes under unsaturated conditions and applied it to a hydrological infiltration experiment performed across a periglacial slope deposit in northwest Luxembourg. Our approach relies on a spatial and temporal quasicontinuous data recording and processing, followed by an attribute analysis based on analyzing differences between individual time steps. The results demonstrate the ability of time-lapse GPR monitoring to visualize the spatial and temporal dynamics of preferential flow processes with a spatial resolution in the order of a few decimeters and temporal resolution in the order of a few minutes. We observe excellent agreement with water table information originating from different boreholes. This demonstrates the potential of surface-based GPR reflection monitoring to observe the spatiotemporal dynamics of water movements in the subsurface. It provides valuable, and so far not accessible, information for example in the field of hydrology and pedology that allows studying the actual subsurface processes rather than deducing them from point information.}, language = {en} } @article{GuillemoteauSimonHulinetal.2019, author = {Guillemoteau, Julien and Simon, Francois-Xavier and Hulin, Guillaume and Dousteyssier, Bertrand and Dacko, Marion and Tronicke, Jens}, title = {3-D imaging of subsurface magnetic permeability/susceptibility with portable frequency domain electromagnetic sensors for near surface exploration}, series = {Geophysical journal international}, volume = {219}, journal = {Geophysical journal international}, number = {3}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {0956-540X}, doi = {10.1093/gji/ggz382}, pages = {1773 -- 1785}, year = {2019}, abstract = {The in-phase response collected by portable loop-loop electromagnetic induction (EMI) sensors operating at low and moderate induction numbers (<= 1) is typically used for sensing the magnetic permeability (or susceptibility) of the subsurface. This is due to the fact that the in-phase response contains a small induction fraction and a preponderant induced magnetization fraction. The magnetization fraction follows the magneto-static equations similarly to the magnetic method but with an active magnetic source. The use of an active source offers the possibility to collect data with several loop-loop configurations, which illuminate the subsurface with different sensitivity patterns. Such multiconfiguration soundings thereby allows the imaging of subsurface magnetic permeability/susceptibility variations through an inversion procedure. This method is not affected by the remnant magnetization and theoretically overcomes the classical depth ambiguity generally encountered with passive geomagnetic data. To invert multiconfiguration in-phase data sets, we propose a novel methodology based on a full-grid 3-D multichannel deconvolution (MCD) procedure. This method allows us to invert large data sets (e.g. consisting of more than a hundred thousand of data points) for a dense voxel-based 3-D model of magnetic susceptibility subject to smoothness constraints. In this study, we first present and discuss synthetic examples of our imaging procedure, which aim at simulating realistic conditions. Finally, we demonstrate the applicability of our method to field data collected across an archaeological site in Auvergne (France) to image the foundations of a Gallo-Roman villa built with basalt rock material. Our synthetic and field data examples demonstrate the potential of the proposed inversion procedure offering new and complementary ways to interpret data sets collected with modern EMI instruments.}, language = {en} } @article{AllroggenBoothBakeretal.2019, author = {Allroggen, Niklas Robin and Booth, Adam D. and Baker, Sandra E. and Ellwood, Stephen A. and Tronicke, Jens}, title = {High-resolution imaging and monitoring of animal tunnels using 3D ground-penetrating radar}, series = {Near surface geophysics}, volume = {17}, journal = {Near surface geophysics}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1569-4445}, doi = {10.1002/nsg.12039}, pages = {291 -- 298}, year = {2019}, abstract = {Ground-penetrating radar is widely used to provide highly resolved images of subsurface sedimentary structures, with implications for processes active in the vadose zone. Frequently overlooked among these structures are tunnels excavated by fossorial animals (e.g., moles). We present two repeated ground-penetrating radar surveys performed a year apart in 2016 and 2017. Careful three-dimensional data processing reveals, in each data set, a pattern of elongated structures that are interpreted as a subsurface mole tunnel network. Our data demonstrate the ability of three-dimensional ground-penetrating radar imaging to non-invasively delineate the small animal tunnels (similar to 5 cm diameter) at a higher spatial and geolocation resolution than has previously been achieved. In turn, this makes repeated surveys and, therefore, long-term monitoring possible. Our results offer valuable insight into the understanding of the near-surface and showcase a potential new application for a geophysical method as well as a non-invasive method of ecological surveying.}, language = {en} } @misc{HugenschmidtGiannopoulosTronicke2019, author = {Hugenschmidt, Johannes and Giannopoulos, Antonios and Tronicke, Jens}, title = {Foreword}, series = {Near surface geophysics}, volume = {17}, journal = {Near surface geophysics}, number = {3}, publisher = {Wiley}, address = {Oxford}, issn = {1569-4445}, doi = {10.1002/nsg.12050}, pages = {199 -- 200}, year = {2019}, language = {en} } @article{KloseGuillemoteauSimonetal.2018, author = {Klose, Tim and Guillemoteau, Julien and Simon, Francois-Xavier and Tronicke, Jens}, title = {Toward subsurface magnetic permeability imaging with electromagnetic induction sensors}, series = {Geophysics}, volume = {83}, journal = {Geophysics}, number = {5}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2017-0827.1}, pages = {E335 -- E345}, year = {2018}, abstract = {In near-surface geophysics, small portable loop-loop electro-magnetic induction (EMI) sensors using harmonic sources with a constant and rather small frequency are increasingly used to investigate the electrical properties of the subsurface. For such sensors, the influence of electrical conductivity and magnetic permeability on the EMI response is well-understood. Typically, data analysis focuses on reconstructing an electrical conductivity model by inverting the out-of-phase response. However, in a variety of near-surface applications, magnetic permeability (or susceptibility) models derived from the in-phase (IP) response may provide important additional information. In view of developing a fast 3D inversion procedure of the IP response for a dense grid of measurement points, we first analyze the 3D sensitivity functions associated with a homogeneous permeable half-space. Then, we compare synthetic data computed using a linear forward-modeling method based on these sensitivity functions with synthetic data computed using full nonlinear forward-modeling methods. The results indicate the correctness and applicability of our linear forward-modeling approach. Furthermore, we determine the advantages of converting IP data into apparent permeability, which, for example, allows us to extend the applicability of the linear forward-modeling method to high-magnetic environments. Finally, we compute synthetic data with the linear theory for a model consisting of a controlled magnetic target and compare the results with field data collected with a four-configuration loop-loop EMI sensor. With this field-scale experiment, we determine that our linear forward-modeling approach can reproduce measured data with sufficiently small error, and, thus, it represents the basis for developing efficient inversion approaches.}, language = {en} } @article{TronickeTrauth2018, author = {Tronicke, Jens and Trauth, Martin H.}, title = {Classroom-sized geophysical experiments}, series = {European Journal of Physics}, volume = {39}, journal = {European Journal of Physics}, number = {3}, publisher = {IOP Publ. Ltd.}, address = {Bristol}, issn = {0143-0807}, doi = {10.1088/1361-6404/aaad5b}, pages = {15}, year = {2018}, abstract = {Modern mobile devices (i.e. smartphones and tablet computers) are widespread, everyday tools, which are equipped with a variety of sensors including three-axis magnetometers. Here, we investigate the feasibility and the potential of using such mobile devices to mimic geophysical experiments in the classroom in a table-top setup. We focus on magnetic surveying and present a basic setup of a table-top experiment for collecting three-component magnetic data across well-defined source bodies and structures. Our results demonstrate that the quality of the recorded data is sufficient to address a number of important basic concepts in the magnetic method. The shown examples cover the analysis of magnetic data recorded across different kinds of dipole sources, thus illustrating the complexity of magnetic anomalies. In addition, we analyze the horizontal resolution capabilities using a pair of dipole sources placed at different horizontal distances to each other. Furthermore, we demonstrate that magnetic data recorded with a mobile device can even be used to introduce filtering, transformation, and inversion approaches as they are typically used when processing magnetic data sets recorded for real-world field applications. Thus, we conclude that such table-top experiments represent an easy-to-implement experimental procedure (as student exercise or classroom demonstration) and can provide first hands-on experience in the basic principles of magnetic surveying including the fundamentals of data acquisition, analysis and processing, as well as data evaluation and interpretation.}, language = {en} } @misc{JackischAngermannAllroggenetal.2017, author = {Jackisch, Conrad and Angermann, Lisa and Allroggen, Niklas and Sprenger, Matthias and Blume, Theresa and Tronicke, Jens and Zehe, Erwin}, title = {Form and function in hillslope hydrology}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {665}, issn = {1866-8372}, doi = {10.25932/publishup-41918}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419188}, pages = {27}, year = {2017}, abstract = {The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR "trenches". We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).}, language = {en} } @misc{AngermannJackischAllroggenetal.2017, author = {Angermann, Lisa and Jackisch, Conrad and Allroggen, Niklas and Sprenger, Matthias and Zehe, Erwin and Tronicke, Jens and Weiler, Markus and Blume, Theresa}, title = {Form and function in hillslope hydrology}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {658}, issn = {1866-8372}, doi = {10.25932/publishup-41916}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419161}, pages = {22}, year = {2017}, abstract = {The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al. (2017).}, language = {en} } @article{GuillemoteauLueckTronicke2017, author = {Guillemoteau, Julien and L{\"u}ck, Erika and Tronicke, Jens}, title = {1D inversion of direct current data acquired with a rolling electrode system}, series = {Journal of applied geophysics}, volume = {146}, journal = {Journal of applied geophysics}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0926-9851}, doi = {10.1016/j.jappgeo.2017.09.010}, pages = {167 -- 177}, year = {2017}, abstract = {Direct current systems employing a kinematic surveying strategy allow to analyze the electrical resistivity of the subsurface for large areas (i.e., several hectares). Typical applications are found in precision agriculture, archaeological prospecting and soil sciences. With the typical survey setting, the collected data sets are often characterized by a rather high level of noise and a rather coarse lateral sampling compared to data acquired with fixed electrodes. We therefore present an efficient one-dimensional inversion approach in which we put special attention on modeling the effects of noise. We apply this method to data recorded with a five-offset equatorial dipole-dipole system employing rolling electrodes. By performing several synthetic tests with realistic noise levels, we found that the considered five-configuration soundings allow for a reliable imaging of two-layer cases in the uppermost two meters of the subsurface, where the subsurface can be assumed to follow a horizontally layered geometry within 3 m around the system. By analyzing the corresponding sensitivity functions, we also show that the equatorial dipole-dipole array is relatively well suited for a 1D inversion approach compared to standard in-line electrode arrays. To illustrate this aspect, we show that our method can provide results similar to those obtained with a 2D Wenner imaging procedure for data recorded across a well-constrained 2D target. We finally apply our method to a large five-offset data set acquired in an agricultural study. The final pseudo-3D model of electrical resistivity is in accordance with borehole data available for the surveyed area. Our results demonstrate the applicability and the versatility of the presented inversion approach for large-scale data sets as they are typically collected with such rolling electrode systems. (C) 2017 Elsevier B.V. All rights reserved.}, language = {en} } @article{GuillemoteauChristensenJacobsenetal.2017, author = {Guillemoteau, Julien and Christensen, Niels Boie and Jacobsen, Bo Holm and Tronicke, Jens}, title = {Fast 3D multichannel deconvolution of electromagnetic induction loop-loop apparent conductivity data sets acquired at low induction numbers}, series = {Geophysics}, volume = {82}, journal = {Geophysics}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2016-0518.1}, pages = {E357 -- E369}, year = {2017}, abstract = {Electromagnetic induction (EMI) sensors using sufficiently low-frequency harmonic sources and sufficiently small loop separations operate in the low-induction-number (LIN) domain for a relatively wide range of background conductivity. These systems are used in diverse near-surface investigations including applications from soil sciences, hydrology, and archaeology. The special case of portable multiconfiguration EMI sensors operating at frequencies <= 20 kHz offers the possibility of using a fast linear deconvolution method to interpret multichannel data sets in three dimensions. Here, we have developed a fast 3D inversion/deconvolution method regularized with 3D smoothness constraints and formulated in the hybrid spectral-spatial domain. Compared with other linear approaches, the spectral-spatial domain formulation significantly reduces the computational cost of the processing and opens the door for real-time 3D interpretation of large data sets consisting of more than 100,000 data points. First, we test our proposed algorithm on synthetic data sets computed with the full Maxwell theory. Then, we apply our method to a real four-configuration EMI data set acquired to map the thickness of peat layers embedded in a sandy environment. For the synthetic and the field example, we compared our result with the result obtained using a standard point-by-point 1D nonlinear inversion approach. This comparison demonstrates that the proposed methodology provides superior lateral resolution compared with the 1D nonlinear inversion, at the same time significantly reducing the computational cost of the processing.}, language = {en} } @article{AngermannJackischAllroggenetal.2017, author = {Angermann, Lisa and Jackisch, Conrad and Allroggen, Niklas and Sprenger, Matthias and Zehe, Erwin and Tronicke, Jens and Weiler, Markus and Blume, Theresa}, title = {Form and function in hillslope hydrology: characterization of subsurface flow based on response observations}, series = {Hydrology and earth system sciences : HESS}, volume = {21}, journal = {Hydrology and earth system sciences : HESS}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-21-3727-2017}, pages = {3727 -- 3748}, year = {2017}, abstract = {The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al. (2017).}, language = {en} }