Author
Daniel Schweizer
Bio: Daniel Schweizer is an academic researcher from Karlsruhe Institute of Technology. The author has contributed to research in topics: Landslide & Data assimilation. The author has an hindex of 3, co-authored 7 publications receiving 48 citations.
Papers
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TL;DR: Wang et al. as discussed by the authors proposed a general framework for analyzing the spatial and temporal evolution of a multi-stage riverbank landslide by integrating large amounts of data from earth surface investigations, subsurface explorations, in-situ monitoring and geological dating.
40 citations
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TL;DR: The study shows that different types of geological data have disparate effects on model uncertainty and model geometry, and the presented approach using both information entropy and distance measures can be a major help in the optimization of 3-D geological models.
Abstract: . The quality of a 3-D geological model strongly depends on the type of integrated geological data, their interpretation and associated uncertainties. In order to improve an existing geological model and effectively plan further site investigation, it is of paramount importance to identify existing uncertainties within the model space. Information entropy, a voxel-based measure, provides a method for assessing structural uncertainties, comparing multiple model interpretations and tracking changes across consecutively built models. The aim of this study is to evaluate the effect of data integration (i.e., update of an existing model through successive addition of different types of geological data) on model uncertainty, model geometry and overall structural understanding. Several geological 3-D models of increasing complexity, incorporating different input data categories, were built for the study site Staufen (Germany). We applied the concept of information entropy in order to visualize and quantify changes in uncertainty between these models. Furthermore, we propose two measures, the Jaccard and the city-block distance, to directly compare dissimilarities between the models. The study shows that different types of geological data have disparate effects on model uncertainty and model geometry. The presented approach using both information entropy and distance measures can be a major help in the optimization of 3-D geological models.
39 citations
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TL;DR: In this article, a closer look at current groundwater monitoring practice reveals the need for updates with a special focus on the benefits of high-frequency and high-resolution datasets, and the authors raise awareness about the necessity for improvement, provide initial recommendations and advocates for the development of universal guidelines.
Abstract: Groundwater is an important global resource and its sustainable use faces major challenges. New methods and advances in computational science could lead to much improved understanding of groundwater processes and subsurface properties. A closer look at current groundwater monitoring practice reveals the need for updates with a special focus on the benefits of high-frequency and high-resolution datasets. To future-proof hydrogeology, this technical note raises awareness about the necessity for improvement, provides initial recommendations and advocates for the development of universal guidelines.
13 citations
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TL;DR: In this article, the authors compare the performance of discrete Fourier transform (DFT) and harmonic least squares (HALS) signal processing methods to extract harmonic component properties from groundwater measurements.
Abstract: The groundwater pressure response to the ubiquitous Earth and atmospheric tides provides a largely untapped opportunity to passively characterize and quantify subsurface hydro-geomechanical properties. However, this requires reliable extraction of closely spaced harmonic components with relatively subtle amplitudes but well-known tidal periods from noisy measurements. The minimum requirements for the suitability of existing groundwater records for analysis are unknown. This work systematically tests and compares the ability of two common signal processing methods, the discrete Fourier transform (DFT) and harmonic least squares (HALS), to extract harmonic component properties. First, realistic conditions are simulated by analyzing a large number of synthetic data sets with variable sampling frequencies, record durations, sensor resolutions, noise levels and data gaps. Second, a model of two real-world data sets with different characteristics is validated. The results reveal that HALS outperforms the DFT in all aspects, including the ability to handle data gaps. While there is a clear trade-off between sampling frequency and record duration, sampling rates should not be less than six samples per day and records should not be shorter than 20 days when simultaneously extracting tidal constituents. The accuracy of detection is degraded by increasing noise levels and decreasing sensor resolution. However, a resolution of the same magnitude as the expected component amplitude is sufficient in the absence of excessive noise. The results provide a practical framework to determine the suitability of existing groundwater level records and can optimize future groundwater monitoring strategies to improve passive characterization using tidal signatures.
8 citations
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TL;DR: In this paper, a study site in Staufen, Germany, where an improper borehole heat exchanger (BHE) installation has allowed ingress of water into the clay-sulfate bearing strata of the Gipskeuper, followed by swelling and substantial heave of the land surface.
8 citations
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199 citations
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01 Jan 2018TL;DR: This chapter provides an entry point to recent developments in geological modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of geological observations and knowledge in geophysical interpretation, modeling and inverse approaches.
Abstract: The Earth below ground is the subject of interest for many geophysical as well as geological investigations. Even though most practitioners would agree that all available information should be used in such an investigation, it is common practice that only a part of geological and geophysical information is actually integrated in structural geological models. We believe that some reasons for this omission are (a) an incomplete picture of available geological modeling methods, and (b) the problem of the perceived static picture of an inflexible geological representation in an image or geological model. With this work, we aim to contribute to the problem of subsurface interface detection through (a) the review of state-of-the-art geological modeling methods that allow the consideration of multiple aspects of geological realism in the form of observations, information, and knowledge, cast in geometric representations of subsurface structures, and (b) concepts and methods to analyze, quantify, and communicate related uncertainties in these models. We introduce a formulation for geological model representation and interpolation and uncertainty analysis methods with the aim to clarify similarities and differences in the diverse set of approaches that developed in recent years. We hope that this chapter provides an entry point to recent developments in geological modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of geological observations and knowledge in geophysical interpretation, modeling and inverse approaches.
110 citations
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TL;DR: This study subdivides a mesoscale catchment into 105 hillslopes and represents each by a two-dimensional numerical hillslope model, and finds that the concept of hydrological similarity is not necessarily time invariant.
Abstract: . The increasing diversity and resolution of spatially
distributed data on terrestrial systems greatly enhance the potential of
hydrological modeling. Optimal and parsimonious use of these data sources
requires, however, that we better understand (a) which system characteristics
exert primary controls on hydrological dynamics and (b) to what level of
detail do those characteristics need to be represented in a model. In this study we develop and test an approach to explore these questions
that draws upon information theoretic and thermodynamic reasoning, using
spatially distributed topographic information as a straightforward example.
Specifically, we subdivide a mesoscale catchment into 105 hillslopes and
represent each by a two-dimensional numerical hillslope model. These
hillslope models differ exclusively with respect to topography-related
parameters derived from a digital elevation model (DEM); the remaining setup and
meteorological forcing for each are identical. We analyze the degree of
similarity of simulated discharge and storage among the hillslopes as a
function of time by examining the Shannon information entropy. We
furthermore derive a “compressed” catchment model by clustering the
hillslope models into functional groups of similar runoff generation using
normalized mutual information (NMI) as a distance measure. Our results reveal that, within our given model environment, only a portion
of the entire amount of topographic information stored within a digital
elevation model is relevant for the simulation of distributed runoff and
storage dynamics. This manifests through a possible compression of the model
ensemble from the entire set of 105 hillslopes to only 6 hillslopes, each
representing a different functional group, which leads to no substantial
loss in model performance. Importantly, we find that the concept of
hydrological similarity is not necessarily time invariant. On the contrary,
the Shannon entropy as measure for diversity in the simulation ensemble
shows a distinct annual pattern, with periods of highly redundant
simulations, reflecting coherent and organized dynamics, and periods where
hillslopes operate in distinctly different ways. We conclude that the proposed approach provides a powerful framework for
understanding and diagnosing how and when process organization and
functional similarity of hydrological systems emerge in time. Our approach
is neither restricted to the model nor to model targets or the data source
we selected in this study. Overall, we propose that the concepts of
hydrological systems acting similarly (and thus giving rise to redundancy)
or displaying unique functionality (and thus being irreplaceable) are not
mutually exclusive. They are in fact of complementary nature, and systems
operate by gradually changing to different levels of organization in time.
46 citations
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TL;DR: The experimental results indicate that IVS-based optimized SVR can significantly improve predictions and the joint mutual information (JMI) and double input symmetrical relevance (DISR) criteria are recommended for IVS for seepage-driven landslides because they achieve the best tradeoff between accuracy and stability.
41 citations
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TL;DR: Wang et al. as discussed by the authors proposed a general framework for analyzing the spatial and temporal evolution of a multi-stage riverbank landslide by integrating large amounts of data from earth surface investigations, subsurface explorations, in-situ monitoring and geological dating.
40 citations