Lithosphere strain rate and stress field orientations near the Alpine arc in Switzerland

Houlié, Nicolas; Woessner, J.; Giardini, Domenico; Rothacher, M.

doi:10.1038/s41598-018-20253-z

Cited by 31 publications

(25 citation statements)

References 92 publications

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“…The regional stress field derived from fault plane estimates (Kastrup et al 2004) points out perturbations with respect to the general European stress field in the vicinity of the Alps. On the regional scale, the uplift rate's spatial gradient was proposed to drive seismicity as well as landslide loci (Jaboyedoff et al 2003). Table 1.…”

Section: Geodynamic and Seismological Settingmentioning

confidence: 99%

“…Mapped faults can be compared to the a compilation of focal mechanisms and the derived stress map (Kastrup et al 2004), and included either as input or as control of 3-D numerical models of geodynamic evolution which can quantify the 3-D stress and strain field (e.g., Lechmann et al 2014;von Tscharner et al 2016). Such models would further characterize the relationship between stress and strain fields in Switzerland, which has been recently analysed by Houlié et al (2018).…”

Section: Kinematic Comparisonmentioning

confidence: 99%

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Spatial relation of surface faults and crustal seismicity: a first comparison in the region of Switzerland

et al. 2018

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The deformation pattern in active orogens is in general diffuse and distributed, and is expressed by spatially scattered seismicity and fault network. We select two relating datasets in the region encompassing Switzerland and analyse how they compare with each other. The datasets are not complete but are the best datasets currently available which fully cover the investigated area at a uniform scale. The distribution of distances from each earthquake to the nearest fault suggests that about two-thirds of the seismicity occurs near faults, yet about 10% occurs far from known faults. These numbers are stable for various selections of earthquakes and even when considering location uncertainties. Earthquake magnitudes in the catalogue are smaller than what could be expected from faults lengths. This suggests that the deep fracture pattern is more segmented than the superficial one, or mostly partial rupture during earthquakes, and (partly) the impropriety of the scaling law. Statistics on the distances from each fault to the nearest earthquake reveal that all supposedly-active faults in Switzerland have experienced a typically felt (magnitude 2.5 or larger) event, and only one out of six has not done so in the past four decades. Future applications of the presented approach to more complete or comprehensive fault databases may result in revised numbers regarding the connection between deep and superficial fracture patterns, representative of the stress regime of the region. The public and educational message: (1) in the region of Switzerland, earthquakes can happen in areas without known or mapped faults; (2) not all faults produce earthquakes within a human lifetime, but they seem to do so over long times.

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Section: Geodynamic and Seismological Settingmentioning

confidence: 99%

Section: Kinematic Comparisonmentioning

confidence: 99%

Spatial relation of surface faults and crustal seismicity: a first comparison in the region of Switzerland

et al. 2018

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“…Our study is focused on France and neighboring Western Europe since they represent an ideal location for testing these methodological developments. Indeed, they are often considered as a domain without significant deformation except in its bordering mountain ranges, the Alps (e.g., Houlié et al, 2018;Brockmann et al, 2012) and the Pyrenees (e.g., Neres et al, 2018;Rigo et al, 2015). The Alps and Pyrenees have a high level of seismic activity ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Extracting small deformation beyond individual station precision from dense GNSS networks in France and Western Europe

Masson

Mazzotti

Vernant

et al. 2019

Preprint

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Abstract. We use dense geodetic networks and large GPS datasets to extract regionally coherent velocities and deformation rates in France and neighboring Western Europe. This analysis is combined with statistical tests on synthetic data to quantify the deformation detection thresholds and significance levels. By combining two distinct methods, Gaussian smoothing and k-means clustering, we extract horizontal deformations with a 95% confidence level ca. 0.1–0.2 mm yr−1 (ca. 0.5–1 × 10-9 yr−1) on spatial scales of 100–200 km or more. From these analyses, we show that the regionally average velocity and strain rate fields are statistically significant in most of our study area. The first order deformation signal in France and neighboring Western Europe is a belt of N-S to NE-SW shortening ca. 0.2–0.4 mm yr−1 (1–2 × 10−9 yr−1) in central and eastern France. In addition to this large-scale signal, patterns of orogen-normal extension are observed in the Alps and the Pyrenees, but methodological biases, mainly related to GPS solution combinations, limit the spatial resolution and preclude associations with specific geological structures. The patterns of deformation in western France show either tantalizing correlation (Brittany) or anti-correlation (Aquitaine Basin) with the seismicity. Overall, more detailed analyses are required to address the possible origin of these signals and the potential role of aseismic deformation.

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“…Another fundamental issue is the representation of the strain-rate state. One of the possible techniques that can help to visualize the deformation rate of the dataset is to plot the main components of the tensor using strain-rate diagrams, where concentrations of strain-rate patterns can be displayed as vector fields (see, for example, the ones in geodetical observations of the Earth's mantle [34][35][36]). The main drawback of strain-rate diagrams is that the strain-rate components are visualized as the projection of three-dimensional vector fields into the two-dimensional framework, and, therefore, the third-dimension component has to be necessarily neglected.…”

Section: Introductionmentioning

confidence: 99%

Visualization of the Strain-Rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description

Salazar-Llano

Bayona-Roa

2019

Applied Sciences

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One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be thought of as a cloud of points that gradually deforms. However, point-wise variations lack information about the overall deformation pattern, and, more importantly, about the extreme deformation locations inside the cloud. This present article applies a technique in computational mechanics to derive the strain-rate state of a time-dependent and three-dimensional data distribution, by which one can characterize its main trends of shift. Indeed, the tensorial analysis methodology is able to determine the global deformation rates in the entire dataset. With the use of this technique, one can characterize the significant fluctuations in a reduced multivariate description of an urban system and identify the possible causes of those changes: calculating the strain-rate state of a PCA-based multivariate description of an urban system, we are able to describe the clustering and divergence patterns between the districts of a city and to characterize the temporal rate in which those variations happen.

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Lithosphere strain rate and stress field orientations near the Alpine arc in Switzerland

Cited by 31 publications

References 92 publications

Spatial relation of surface faults and crustal seismicity: a first comparison in the region of Switzerland

Spatial relation of surface faults and crustal seismicity: a first comparison in the region of Switzerland

Extracting small deformation beyond individual station precision from dense GNSS networks in France and Western Europe

Visualization of the Strain-Rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description

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