Quaternary deposits: concept for a stratigraphic classification and nomenclature—an example from northern Switzerland

Graf, H.; Burkhalter, Reto

doi:10.1007/s00015-016-0222-7

Cited by 21 publications

(12 citation statements)

References 8 publications

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“…Geological units modified from the Geological Atlas of Switzerland (Ludwig, 1930;Geiger, 1943Geiger, , 1968Eugster et al, 1960;Hübscher, 1961;Saxer, 1965;Hofmann, 1967Hofmann, , 1973Hofmann, , 1981Hofmann, , 1993Hofmann, , 1997Hottinger et al, 1970;Pavoni et al, 1992;Hantke, 2003;Wyssling, 2007;Zaugg, 2007;Zaugg and Geyer, 2008;Rey et al, 2011;Haldimann et al, 2017) and the Geological Map of Baden-Württemberg (Regierungspräsidium Freiburg Landesamt für Geologie, Rohstoffe und Bergbau, 2013). Niederterrasse refers to Late Pleistocene sediments, Hochterrasse and Deckenschotter to Middle Pleistocene and Early Pleistocene, respectively (Graf and Burkhalter, 2016). Cities: Af: Andelfingen, BWs: Bad Waldsee, BZ: Bregenz, E: Engen, Ff: Frauenfeld, IiA: Isny im Allgäu, K: Konstanz, Ki: Kißlegg, LiA: Leutkirch im Allgäu, Mkf: Markelfingen, Os: Ostrach, R: Ravensburg, Rü: Rüdlingen, SH: Schaffhausen, Si: Singen, St: Steißlingen, Sto: Stockach, StR: Stein am Rhein.…”

Section: Tableunclassified

“…(north of Stein am Rhein) to ~720 m a.s.l. (north of Markelfingen), as deduced from the elevation of interpreted LGM till overlying Deckenschotter (Graf and Burkhalter, 2016) and other pre-LGM deposits and bedrock (cf. Schreiner, 1992a;Keller and Krayss, 2005b;Bini et al, 2009).…”

Section: Rhine Glacier Dynamics During the Lgmmentioning

confidence: 99%

“…Geological units modified from the Geological Atlas of Switzerland(Jäckli, 1966;Diebold et al, 2005;Graf et al, 2007Graf et al, , 2012Jordan et al, 2011; Gubler, 2020b). Niederterrasse refers to Late Pleistocene sediments, Hochterrasse to Middle Pleistocene, respectively(Graf and Burkhalter, 2016). Indicated cross-sections (B-B ′ , C-C ′ ) are shown in Fig.10a,b, respectively.…”

mentioning

confidence: 99%

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Last Glacial Maximum glacier fluctuations on the northern Alpine foreland: Geomorphological and chronological reconstructions from the Rhine and Reuss glacier systems

et al. 2023

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Section: Tableunclassified

Section: Rhine Glacier Dynamics During the Lgmmentioning

confidence: 99%

mentioning

confidence: 99%

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Last Glacial Maximum glacier fluctuations on the northern Alpine foreland: Geomorphological and chronological reconstructions from the Rhine and Reuss glacier systems

et al. 2023

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“…An upper fluvial deposit layer of a few dozen meters overlays a thick lacustrine clay layer. The geological context of the area is briefly described in Schorpp et al (2022) or Graf and Burkhalter (2016). The upper fluvial deposit may show locally few superficial clay layers.…”

Section: Test Cases Conceptual Modelmentioning

confidence: 99%

Stochastic multi-fidelity joint hydrogeophysical inversion of consistent geological models

Néven

Schorpp²,

Renard³

2022

Front. Water

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In Quaternary deposits, the characterization of subsurface heterogeneity and its associated uncertainty is critical when dealing with groundwater resource management. The combination of different data types through joint inversion has proven to be an effective way to reduce final model uncertainty. Moreover, it allows the final model to be in agreement with a wider spectrum of data available on site. However, integrating them stochastically through an inversion is very time-consuming and resource expensive, due to the important number of physical simulations needed. The use of multi-fidelity models, by combining low-fidelity inexpensive and less accurate models with high-fidelity expensive and accurate models, allows one to reduce the time needed for inversion to converge. This multiscale logic can be applied for the generation of Quaternary models. Most Quaternary sedimentological models can be considered as geological units (large scale), populated with facies (medium scale), and finally completed by physical parameters (small scale). In this paper, both approaches are combined. A simple and fast time-domain EM 1D geophysical direct problem is used to first constrain a simplified stochastic geologically consistent model, where each stratigraphic unit is considered homogeneous in terms of facies and parameters. The ensemble smoother with multiple data assimilation (ES-MDA) algorithm allows generating an ensemble of plausible subsurface realizations. Fast identification of the large-scale structures is the main point of this step. Once plausible unit models are generated, high-fidelity transient groundwater flow models are incorporated. The low-fidelity models are populated stochastically with heterogeneous facies and their associated parameter distribution. ES-MDA is also used for this task by directly inferring the property values (hydraulic conductivity and resistivity) from the generated model. To preserve consistency, geophysical and hydrogeological data are inverted jointly. This workflow ensures that the models are geologically consistent and are therefore less subject to artifacts due to localized poor-quality data. It is able to robustly estimate the associated uncertainty with the final model. Finally, due to the simplification of both the direct problem and the geology during the low-fidelity part of the inversion, it greatly reduces the time required to converge to an ensemble of complex models while preserving consistency.

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“…The Upper Aare Valley presents a typical Quaternary geology for alpine valleys: the basement is usually a few hundred meters deep and is covered with a complex interwinding of glacial, fluvio-glacial, and fluvial deposits 38 , 39 . Multiple cycles of glacial advances and retreats have been identified in the Swiss basin, causing multiple changes in the deposition processes 40 . In the particular case of the Upper Aare Valley, at least four glacial cycles have been identified in boreholes 41 .…”

Section: Application On the Aare Valleymentioning

confidence: 99%

Automatic stochastic 3D clay fraction model from tTEM survey and borehole data

Néven

Christiansen

Renard

2022

Sci Rep

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In most urbanized and agricultural areas of central Europe, the shallow underground is constituted of Quaternary deposits which are often the most extensively used layers (water pumping, shallow geothermic, material excavation). All these deposits are often complexly intertwined, leading to high spatial variability and high complexity. Geophysical data can be a fast and reliable source of information about the underground. Still, the integration of these data can be time-consuming, it lacks realistic interpolation in a full 3D space, and the final uncertainty is often not represented. In this study, we propose a new methodology to combine boreholes and geophysical data with uncertainty in an automatic framework. A spatially varying translator function that predicts the clay fraction from resistivity is inverted using boreholes description as control points. It is combined with a 3D stochastic interpolation framework based on a Multiple Points Statistics algorithm and Gaussian Random Function. This novel workflow allows incorporating robustly the data and their uncertainty and requires less user intervention than the already existing workflows. The methodology is illustrated for ground-based towed transient electromagnetic data (tTEM) and borehole data from the upper Aare valley, Switzerland. In this location, a 3D realistic high spatial resolution model of clay fraction was obtained over the whole valley. The very dense data set allowed to demonstrate the quality of the predicted values and their corresponding uncertainties using cross-validation.

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Quaternary deposits: concept for a stratigraphic classification and nomenclature—an example from northern Switzerland

Cited by 21 publications

References 8 publications

Last Glacial Maximum glacier fluctuations on the northern Alpine foreland: Geomorphological and chronological reconstructions from the Rhine and Reuss glacier systems

Last Glacial Maximum glacier fluctuations on the northern Alpine foreland: Geomorphological and chronological reconstructions from the Rhine and Reuss glacier systems

Stochastic multi-fidelity joint hydrogeophysical inversion of consistent geological models

Automatic stochastic 3D clay fraction model from tTEM survey and borehole data

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