ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2022-01-05
    Description: Abstract
    Description: The Central Andean orogeny is caused by the subduction of the Nazca oceanic plate beneath the South-American continental plate. In Particular, the Southern Central Andes (SCA, 27°-40°S) are characterized by a strong N-S and E-W variation in the crustal deformation style and intensity. Despite being the surface geology relatively well known, the information on the deep structure of the upper plate in terms of its thickness and density configurations is still scarcely constrained. Previous seismic studies have focused on the crustal structure of the northern part of the SCA (~27°-33°S) based upon 2D cross-sections, while 3D crustal models centred on the South-American or the Nazca Plate have been published with lower resolution. To gain insight into the present-day state of the lithosphere in the area, we derived a 3D model that is consistent with both the available geological and seismic data and with the observed gravity field. The model consists on a continental plate with sediments, a two-layer crust and the lithospheric mantle being subducted by an oceanic plate. The model extension covers an area of 700 km x 1100 km, including the orogen, the forearc and the forelands.
    Description: Methods
    Description: Different data sets were integrated to derive the lithospheric features: - We used the global relief model of ETOPO1 (Amante and Eakins 2009) for the topography and bathymetry. - The sub-surface structures were defined by integrating seismically constrained models, including the South-American crustal thickness of Assumpção et al. (2013; model A; 0.5 degree resolution), the sediment thickness of CRUST1 (Laske et al. 2013) and the slab geometry of SLAB2 (Hayes et al. 2018). - Additionally, we included seismic reflection and refraction profiles performed on the Chile margin (Araneda et al. 2003; Contreras-Reyes et al. 2008, 2014, 2015; Flueh et al. 1998; Krawzyk et al. 2006; Moscoso et al. 2011; Sick et al. 2006; Von Huene et al. 1997). - Besides, we used sediment thickness maps from the intracontinental basin database ICONS (6 arc minute resolution, Heine 2007) and two oceanic sediment compilations: one along the southern trench axis (Völker et al. 2013) and another of global-scale (GlobSed; Straume et al. 2019). To build the interfaces between the main lithospheric features, we compiled and interpolated these datasets on a regular grid with a surface resolution of 25 km. For that purpose, the convergent algorithm of the software Petrel was used. We assigned constant densities within each layer, except for the lithospheric mantle. In this case, we implemented a heterogeneous distribution by converting s-wave velocities from the SL2013sv seismic tomography (Schaeffer and Lebedev 2013) to densities. The python tool VelocityConversion was used for the conversion (Meeßen 2017). To further constrain the crustal structure of the upper plate, a gravity forward modelling was carried out using IGMAS+ (Schmidt et al. 2010). The gravity anomaly from the model (calculated gravity) was compared to the free-air anomaly from the global gravity model EIGEN-6C4 (observed gravity; Förste et al 2014; Ince et al. 2019). Subsequently, the crystalline crust of the upper plate was split vertically into two layers of different densities. We inverted the residual between calculated and observed gravity to compute the depth to the interface between the two crustal layers. For the inverse modelling of the gravity residual, the Python package Fatiando a Terra was used (Uieda et al. 2013) For each layer, the depth to the top surface, thickness and density can be found as separate files. All files contain identical columns: - Northing as "X Coord (UTM zone 19S)"; - Easting as "Y Coord (UTM zone 19S)"; - depth to the top surface as "Top (m.a.s.l)" and - thickness of each layer as "Thickness (m)". The header ‘Density’ indicates the bulk density of each unit in kg/m3. For the oceanic and continental mantle units, a separate file is provided with a regular grid of the density distribution with a lateral resolution of 8 km x 9 km and a vertical resolution of 5 km. The containing columns are: Northing as "X Coord (UTM zone 19S)"; Easting as "Y Coord (UTM zone 19S)"; depth as "Depth (m.a.s.l)" and density as "Density (kg/m3)"
    Keywords: Lithosphere ; Gravity Modelling ; Andes ; EARTH SCIENCE ; EARTH SCIENCE 〉 LAND SURFACE 〉 TOPOGRAPHY 〉 TOPOGRAPHICAL RELIEF ; EARTH SCIENCE 〉 OCEANS 〉 BATHYMETRY/SEAFLOOR TOPOGRAPHY 〉 BATHYMETRY ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC PROCESSES 〉 SUBDUCTION ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD ; EARTH SCIENCE 〉 SOLID EARTH 〉 GRAVITY/GRAVITATIONAL FIELD 〉 GRAVITY ; EARTH SCIENCE 〉 SOLID EARTH 〉 ROCKS/MINERALS/CRYSTALS 〉 SEDIMENTS ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Dataset , Dataset
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2022-03-22
    Description: Abstract
    Description: Despite the amount of research focused on the Alpine orogen, significant unknowns remain regarding the thermal field and long term lithospheric strength in the region. Previous published interpretations of these features primarily concern a limited number of 2D cross sections, and those that represent the region in 3D typically do not conform to measured data such as wellbore or seismic measurements. However, in the light of recently published higher resolution region specific 3D geophysical models, that conform to secondary data measurements, the generation of a more up to date revision of the thermal field and long term lithospheric yield strength is made possible, in order to shed light on open questions of the state of the orogen. The study area of this work focuses on a region of 660 km x 620 km covering the vast majority of the Alps and their forelands, with the Central and Eastern Alps and the northern foreland being the best covered regions.
    Keywords: Alps ; Forelands ; Po Basin ; Molasse Basin ; Upper Rhine Graben ; Ivrea Body ; European Crust ; Adriatic Crust ; Sediment Thickness ; Crustal Thickness ; Vosges Massif ; Black Forest Massif ; Bohemian Massif ; Mantle Density ; 4DMB ; Mountain Building Processes in 4d ; EARTH SCIENCE ; EARTH SCIENCE 〉 SOLID EARTH ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOMORPHIC LANDFORMS/PROCESSES 〉 TECTONIC LANDFORMS 〉 MOUNTAINS ; EARTH SCIENCE 〉 SOLID EARTH 〉 GEOTHERMAL DYNAMICS 〉 GEOTHERMAL TEMPERATURE ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS ; lithosphere ; lithosphere 〉 earth's crust ; lithosphere 〉 earth's crust 〉 continental shelf 〉 continent ; lithosphere 〉 earth's crust 〉 sedimentary basin ; physical property 〉 viscosity ; science 〉 natural science 〉 earth science 〉 geophysics
    Type: Dataset , Dataset
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2022-05-13
    Description: Abstract
    Description: Bedload transport is a key process in fluvial morphodynamics and hydraulic engineering, but is notoriously difficult to measure. The recent advent of stream-side seismic monitoring techniques provides an alternative to in-stream monitoring techniques, which are often costly, staff-intensive, and cannot be deployed during large floods. Seismic monitoring is a surrogate method requiring several steps to convert seismic data into bedload data. State-of-the-art approaches of conversion exploit physical models predicting the seismic signal generated by bedload transport. Here, we did an active seismic survey (2017-11) and used seismic data from a flood event (2016-02-22) on the Nahal Ehstemoa to constrain a seismic bedload model. We conducted the active seismic survey to determine the local seismic ground properties, i.e., the Green’s function. We also used water depth and bedload grain size distribution to constrain the seismic bedload model and were able to compare the bedload flux obtained from the seismic data using the model with high-quality independent bedload measurements from slot samplers on the site. The complementary non-seismic data is published in a separate data publication (Lagarde et al., 2020).
    Keywords: Ground properties ; Green’s function ; Environmental seismology ; EARTH SCIENCE 〉 SOLID EARTH ; geology
    Type: Dataset , Dataset
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2022-11-03
    Description: Other
    Description: In the data set we provide both mantle velocity and maximum principal stress orientation resulting from a geodynamical model. The data are calculated with use of the ProSpher 3D code in a spectral domain by spherical harmonics decomposition. The resolution of the model is of 120 spherical harmonics laterally and 50 km in depth. For velocity data (file set: Petrunin-etal19-Vel_XXX.dat), the 1st column represents longitude, 2nd column – latitude, 3d, 4th , 5th – longitudinal, latitudinal, and radial components of velocity in mm/yr, correspondingly. For maximum principal stress orientation data (file set: Petrunin-etal19-SH_XXX.dat), the 1st column represents longitude, 2nd column – latitude, 3d, 4th – longitudinal and latitudinal components of the unit vector representing maximum principal stress direction.
    Keywords: Geodynamic model ; calculated velocity field ; maximum principal stress ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS 〉 PLATE TECTONICS 〉 STRESS ; EARTH SCIENCE 〉 SOLID EARTH 〉 TECTONICS ; EARTH SCIENCE 〉 SOLID EARTH
    Type: Dataset
    Format: 1 Files
    Format: application/octet-stream
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...