@article{ZeheEhretPfisteretal.2014, author = {Zehe, E. and Ehret, U. and Pfister, L. and Blume, Theresa and Schroeder, Boris and Westhoff, M. and Jackisch, C. and Schymanski, Stanislauv J. and Weiler, M. and Schulz, K. and Allroggen, Niklas and Tronicke, Jens and van Schaik, Loes and Dietrich, Peter and Scherer, U. and Eccard, Jana and Wulfmeyer, Volker and Kleidon, Axel}, title = {HESS Opinions: From response units to functional units: a thermodynamic reinterpretation of the HRU concept to link spatial organization and functioning of intermediate scale catchments}, series = {Hydrology and earth system sciences : HESS}, volume = {18}, journal = {Hydrology and earth system sciences : HESS}, number = {11}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-18-4635-2014}, pages = {4635 -- 4655}, year = {2014}, abstract = {According to Dooge (1986) intermediate-scale catchments are systems of organized complexity, being too organized and yet too small to be characterized on a statistical/conceptual basis, but too large and too heterogeneous to be characterized in a deterministic manner. A key requirement for building structurally adequate models precisely for this intermediate scale is a better understanding of how different forms of spatial organization affect storage and release of water and energy. Here, we propose that a combination of the concept of hydrological response units (HRUs) and thermodynamics offers several helpful and partly novel perspectives for gaining this improved understanding. Our key idea is to define functional similarity based on similarity of the terrestrial controls of gradients and resistance terms controlling the land surface energy balance, rainfall runoff transformation, and groundwater storage and release. This might imply that functional similarity with respect to these specific forms of water release emerges at different scales, namely the small field scale, the hillslope, and the catchment scale. We thus propose three different types of "functional units" - specialized HRUs, so to speak - which behave similarly with respect to one specific form of water release and with a characteristic extent equal to one of those three scale levels. We furthermore discuss an experimental strategy based on exemplary learning and replicate experiments to identify and delineate these functional units, and as a promising strategy for characterizing the interplay and organization of water and energy fluxes across scales. We believe the thermodynamic perspective to be well suited to unmask equifinality as inherent in the equations governing water, momentum, and energy fluxes: this is because several combinations of gradients and resistance terms yield the same mass or energy flux and the terrestrial controls of gradients and resistance terms are largely independent. We propose that structurally adequate models at this scale should consequently disentangle driving gradients and resistance terms, because this optionally allow sequifinality to be partly reduced by including available observations, e. g., on driving gradients. Most importantly, the thermodynamic perspective yields an energy-centered perspective on rainfall-runoff transformation and evapotranspiration, including fundamental limits for energy fluxes associated with these processes. This might additionally reduce equifinality and opens up opportunities for testing thermodynamic optimality principles within independent predictions of rainfall-runoff or land surface energy exchange. This is pivotal to finding out whether or not spatial organization in catchments is in accordance with a fundamental organizing principle.}, language = {en} } @article{TronickeVillamorGreen2006, author = {Tronicke, Jens and Villamor, P and Green, Alan G.}, title = {Detailed shallow geometry and vertical displacement estimates of the Maleme Fault Zone, New Zealand, using 2D and 3D georadar}, year = {2006}, abstract = {In an attempt to map the shallow geometry of the Maleme Fault Zone (North Island, New Zealand) and estimate vertical displacements of selected fault strands, we have collected 2D and 3D georadar data using 100 MHz antennae. The 2D data consisted of three parallel georadar lines recorded perpendicular to the axis of the well-defined graben of the Maleme Fault Zone. These similar to 160 in long lines, which were 7.5 m apart, crossed several fault strands on either side of the graben axis. The processed georadar sections revealed two prominent parallel reflections that originated from the boundaries of Late Pleistocene lacustrine and tephra deposits. Distinct vertical offsets of these reflections allowed us to estimate displacernents at individual fault strands across the entire inner graben. The total displacements represented by these offsets was similar to 10-20\% greater than that inferred from geomorphological studies, thus demonstrating the limitations of surface observations for determining cumulative fault movements. The 3D georadar data set, recorded across an area of similar to 70x similar to 20 in to one side of the graben axis, provided key details on individual fault strands. For the 3D visualization of fault-related structures, various spatial attribute analyses based on the cosine of the instantaneous phase proved to be useful}, 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} } @article{TronickePaascheBoeniger2012, author = {Tronicke, Jens and Paasche, Hendrik and B{\"o}niger, Urs}, title = {Crosshole traveltime tomography using particle swarm optimization a near-surface field example}, series = {Geophysics}, volume = {77}, journal = {Geophysics}, number = {1}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2010-0411.1}, pages = {R19 -- R32}, year = {2012}, abstract = {Particle swarm optimization (PSO) is a relatively new global optimization approach inspired by the social behavior of bird flocking and fish schooling. Although this approach has proven to provide excellent convergence rates in different optimization problems, it has seldom been applied to inverse geophysical problems. Until today, published geophysical applications mainly focus on finding an optimum solution for simple, 1D inverse problems. We have applied PSO-based optimization strategies to reconstruct 2D P-wave velocity fields from crosshole traveltime data sets. Our inversion strategy also includes generating and analyzing a representative ensemble of acceptable models, which allows us to appraise uncertainty and nonuniqueness issues. The potential of our strategy was tested on field data collected at a well-constrained test site in Horstwalde, Germany. At this field site, the shallow subsurface mainly consists of sand- and gravel-dominated glaciofluvial sediments, which, as known from several boreholes and other geophysical experiments, exhibit some well-defined layering at the scale of our crosshole seismic data. Thus, we have implemented a flexible, layer-based model parameterization, which, compared with standard cell-based parameterizations, allows for significantly reducing the number of unknown model parameters and for efficiently implementing a priori model constraints. Comparing the 2D velocity fields resulting from our PSO strategy to independent borehole and direct-push data illustrated the benefits of choosing an efficient global optimization approach. These include a straightforward and understandable appraisal of nonuniqueness issues as well as the possibility of an improved and also more objective interpretation.}, language = {en} } @article{TronickePaasche2017, author = {Tronicke, Jens and Paasche, Hendrik}, title = {Integrated interpretation of 2D ground-penetrating radar, P-, and S-wave velocity models in terms of petrophysical properties}, series = {Interpretation : a journal of subsurface characterization}, volume = {5}, journal = {Interpretation : a journal of subsurface characterization}, number = {1}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {2324-8858}, doi = {10.1190/INT-2016-0081.1}, pages = {T121 -- T130}, year = {2017}, abstract = {Near-surface geophysical techniques are extensively used in a variety of engineering, environmental, geologic, and hydrologic applications. While many of these applications ask for detailed, quantitative models of selected material properties, geophysical data are increasingly used to estimate such target properties. Typically, this estimation procedure relies on a two-step workflow including (1) the inversion of geophysical data and (2) the petrophysical translation of the inverted parameter models into the target properties. Standard deterministic implementations of such a quantitative interpretation result in a single best-estimate model, often without considering and propagating the uncertainties related to the two steps. We address this problem by using a rather novel, particle-swarm-based global joint strategy for data inversion and by implementing Monte Carlo procedures for petrophysical property estimation. We apply our proposed workflow to crosshole ground-penetrating radar, P-, and S-wave data sets collected at a well-constrained test site for a detailed geotechnical characterization of unconsolidated sands. For joint traveltime inversion, the chosen global approach results in ensembles of acceptable velocity models, which are analyzed to appraise inversion-related uncertainties. Subsequently, the entire ensembles of inverted velocity models are considered to estimate selected petrophysical properties including porosity, bulk density, and elastic moduli via well-established petrophysical relations implemented in a Monte Carlo framework. Our results illustrate the potential benefit of such an advanced interpretation strategy; i.e., the proposed workflow allows to study how uncertainties propagate into the finally estimated property models, while concurrently we are able to study the impact of uncertainties in the used petrophysical relations (e.g., the influence of uncertain, user-specified parameters). We conclude that such statistical approaches for the quantitative interpretation of geophysical data can be easily extended and adapted to other applications and geophysical methods and might be an important step toward increasing the popularity and acceptance of geophysical tools in engineering practice.}, language = {en} } @article{TronickeHamann2014, author = {Tronicke, Jens and Hamann, G{\"o}ran}, title = {Vertical radar profiling: Combined analysis of traveltimes, amplitudes, and reflections}, series = {Geophysics}, volume = {79}, journal = {Geophysics}, number = {4}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2013-0428.1}, pages = {H23 -- H35}, year = {2014}, abstract = {Vertical radar profiling (VRP) is a single-borehole geophysical technique, in which the receiver antenna is located within a borehole and the transmitter antenna is placed at one or various offsets from the borehole. Today, VRP surveying is primarily used to derive 1D velocity models by inverting the arrival times of direct waves. Using field data collected at a well-constrained test site in Germany, we evaluated a VRP workflow relying on the analysis of direct-arrival traveltimes and amplitudes as well as on imaging reflection events. To invert our VRP traveltime data, we used a global inversion strategy resulting in an ensemble of acceptable velocity models, and thus, it allowed us to appraise uncertainty issues in the estimated velocities as well as in porosity models derived via petrophysical translations. In addition to traveltime inversion, the analysis of direct-wave amplitudes and reflection events provided further valuable information regarding subsurface properties and architecture. The used VRP amplitude preprocessing and inversion procedures were adapted from raybased crosshole ground-penetrating radar (GPR) attenuation tomography and resulted in an attenuation model, which can be used to estimate variations in electrical resistivity. Our VRP reflection imaging approach relied on corridor stacking, which is a well-established processing sequence in vertical seismic profiling. The resulting reflection image outlines bounding layers and can be directly compared to surface-based GPR reflection profiling. Our results of the combined analysis of VRP, traveltimes, amplitudes, and reflections were consistent with independent core and borehole logs as well as GPR reflection profiles, which enabled us to derive a detailed hydro-stratigraphic model as needed, for example, to understand and model groundwater flow and transport.}, language = {en} } @article{TronickeBoeniger2015, author = {Tronicke, Jens and Boeniger, Urs}, title = {Denoising magnetic data using steering kernel regression}, series = {Near surface geophysics}, volume = {13}, journal = {Near surface geophysics}, number = {1}, publisher = {European Association of Geoscientists \& Engineers}, address = {Houten}, issn = {1569-4445}, doi = {10.3997/1873-0604.2014038}, pages = {33 -- 44}, year = {2015}, abstract = {Ground-based magnetic surveying is a common geophysical method to explore near-surface environments in a non-destructive manner. In many typical applications (such as archaeological prospection), the resulting anomaly maps are often characterized by low signal-to-noise ratios and, thus, the suppression of noise is a key step in data processing. Here, we propose the steering kernel regression (SKR) method to denoise magnetic data sets. SKR has been recently developed to suppress random noise in images and video sequences. The core of the method is the steering kernel function which represents a robust estimate of local image structure. Using such a kernel within an iterative regression based denoising framework, helps to minimize image blurring and to preserve the underlying structures such as edges and corners. Because such filter characteristics are desirable for random noise attenuation in potential field data sets, we apply the SKR method for processing high-resolution ground-based magnetic data as they are typically collected in archaeological applications. We test and evaluate the SKR method using synthetic and field data examples and also compare it to more commonly employed denoising strategies relying, for example, on fixed filter masks (e.g., Gaussian filters). Our results show that the SKR method is successful in removing random and acquisition related noise present in our data. Concurrently, it preserves the local image structure including the amplitudes of anomalies. As demonstrated by derivative based transformations, the mentioned filter characteristics significantly impact subsequent processing steps and, therefore, result in an improved analysis and interpretation of magnetic data. Thus, the method can be considered as a promising and novel approach for denoising ground-based magnetic data.}, 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{TronickeAllroggen2015, author = {Tronicke, Jens and Allroggen, Niklas}, title = {Toward automated delineation of ground-penetrating radar facies in clastic sediments: An example from stratified glaciofluvial deposits}, series = {Geophysics}, volume = {80}, journal = {Geophysics}, number = {4}, publisher = {Society of Exploration Geophysicists}, address = {Tulsa}, issn = {0016-8033}, doi = {10.1190/GEO2015-0188.1}, pages = {A89 -- A94}, year = {2015}, abstract = {Ground-penetrating radar (GPR) is an established geophysical method to explore near-surface sedimentary environments. Interpreting GPR images is largely based on manual procedures following concepts known as GPR facies analysis. We have developed a novel strategy to distinguish GPR facies in a largely automated and more objective manner. First, we calculate 13 textural attributes to quantify GPR reflection characteristics. Then, this database is reduced using principal component analysis. Finally, we image the dominating principal components using composite imaging and classify them using standard clustering methods. The potential of this work-flow is evaluated using a 2D GPR field example collected across stratified glaciofluvial deposits. Our results demonstrate that the derived facies images are well correlated with the composition and the porosity of the sediments as known from independent borehole logs. Our analysis strategy eases and improves the interpretability of GPR data and will help in a variety of geologic and hydrological problems.}, language = {en} } @article{SchmelzbachTronickeDietrich2012, author = {Schmelzbach, C. and Tronicke, Jens and Dietrich, P.}, title = {High-resolution water content estimation from surface-based ground-penetrating radar reflection data by impedance inversion}, series = {Water resources research}, volume = {48}, journal = {Water resources research}, number = {31}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2012WR011955}, pages = {16}, year = {2012}, abstract = {Mapping hydrological parameter distributions in high resolution is essential to understand and simulate groundwater flow and contaminant transport. Of particular interest is surface-based ground-penetrating radar (GPR) reflection imaging in electrically resistive sediments because of the expected close link between the subsurface water content and the dielectric permittivity, which controls GPR wave velocity and reflectivity. Conventional tools like common midpoint (CMP) velocity analysis provide physical parameter models of limited resolution only. We present a novel reflection amplitude inversion workflow for surface-based GPR data capable of resolving the subsurface dielectric permittivity and related water content distribution with markedly improved resolution. Our scheme is an adaptation of a seismic reflection impedance inversion scheme to surface-based GPR data. Key is relative-amplitude-preserving data preconditioning including GPR deconvolution, which results in traces with the source-wavelet distortions and propagation effects largely removed. The subsequent inversion for the underlying dielectric permittivity and water content structure is constrained by in situ dielectric permittivity data obtained by direct-push logging. After demonstrating the potential of our novel scheme on a realistic synthetic data set, we apply it to two 2-D 100 MHz GPR profiles acquired over a shallow sedimentary aquifer resulting in water content images of the shallow (3-7 m depth) saturated zone having decimeter resolution.}, language = {en} }