Other language confidence: 0.9510621136923103
This dataset provides point-shapefiles and geotiffs, related to the figures presented in (Frick et al., 2022a, 2022b). It covers most of northern Germany, with the boundaries defined by the extent of the North German Basin, which is part of the Central European Basin System. The files contain information on the depth (m.b.s. = meter below surface), thickness, temperature, heat in place and heat storage potential of selected geological units and the formations therein. These data are an addendum to the data presented in (Frick et al., 2022a, 2022b), resolving 5 geological units and 9 formations. The data are presented as regularly spaced point-shapefiles, with a spacing of 1000 m. The data were produced as part of the Helmholtz Climate Initiative (HICAM), which focuses on Net Zero 2050 (mitigation) and Adapting to Extreme Events (adaptation). As part of this initiative, estimates of the heat in place and heat storage potential of the subsurface play an important part for mitigation of fossil fuel bound emissions as they pose a promising alternative (geothermal energy). The data presented here, therefore give an overview of areas which might be suited for geothermal applications in the different geothermal target units and formations. We integrated the recently published TUNB Model (BGR et al., 2021) as well as available borehole data, data from the Sandsteinfazies and GeoPoNDD projects (Franz et al., 2018, 2015) and temperature data from two models (Agemar et al., 2014; Frick et al., 2021) the process of which will be described in the following.
Concentrations of in-situ-produced cosmogenic 10Be in river sediment are widely used to estimate catchment-average denudation rates. Typically, the 10Be concentrations are measured in the sand fraction of river sediment. However, the grain size of bedload sediment in most bedrock rivers covers a much wider range. Where 10Be concentrations depend on grain size, denudation rate estimates based on the sand fraction alone are potentially biased. To date, knowledge about catchment attributes that may induce grain-size-dependent 10Be concentrations is incomplete or has only been investigated in modelling studies. Here we present an empirical study on the occurrence of grain-size-dependent 10Be concentrations and the potential controls of hillslope angle, precipitation, lithology, and abrasion. We first conducted a study focusing on the sole effect of precipitation in four granitic catchments located on a climate gradient in the Chilean Coastal Cordillera. We found that observed grain size dependencies of 10Be concentrations in the most-arid and most-humid catchments could be explained by the effect of precipitation on both the scouring depth of erosion processes and the depth of the mixed soil layer. Analysis of a global dataset of published 10Be concentrations in different grain sizes (n=73 catchments) – comprising catchments with contrasting hillslope angles, climate, lithology, and catchment size – revealed a similar pattern. Lower 10Be concentrations in coarse grains (defined as “negative grain size dependency”) emerge frequently in catchments which likely have thin soil and where deep-seated erosion processes (e.g. landslides) excavate grains over a larger depth interval. These catchments include steep (> 25°) and humid catchments (> 2000mm yr-1). Furthermore, we found that an additional cause of negative grain size dependencies may emerge in large catchments with weak lithologies and long sediment travel distances (> 2300–7000 m, depending on lithology) where abrasion may lead to a grain size distribution that is not representative for the entire catchment. The results of this study can be used to evaluate whether catchment-average denudation rates are likely to be biased in particular catchments.Samples from the Chilean Coastal Cordillera were processed in the Helmholtz Laboratory for the Geochemistry of the Earth Surface (HELGES). 10Be/9Be ratios were measured at the University of Cologne and normalized to the KN01-6-2 and KN01-5-3 standards. Denudation rates were calculated using a time-independent scaling scheme according to Lal (1991) and Stone (2002) (St scaling scheme) and the SLHL production rate of 4.01 at g-1 yr-1 as reported by Phillips et al. (2016)The global compilation exists of studies that measured 10Be concentrations in different grain sizes from the same sample location. We only included river basins of <5000 km2 which measured 10Be concentrations in at least one sand-sized fraction <2 mm and at least one coarser fraction >2 mm. Catchment parameters have been recalculated using a 90-m SRTM DEM.The data are presented in Excel and csv tables. Table S1 describes the characteristics of the samples catchments, Table S2 includes the grain size dependent 10Be-concentrations measured during this study and Table 3 the global compilation of grain size dependent 10Be-concentrations. All samples of this study (the Chilean Coastal Cordillera) are assigned with International Geo Sample Numbers (IGSN). The IGSN links are included in Table S2 and in the Related References Section on the DOI Landing Page. The data are described in detail in the data description file and in van Dongen et al. (2018) to which they are supplementary material to.
We provide a set of grid files that collectively allow recreating a 3D geological model which covers the Central European Basin System and adjacent areas. The data publication is a complement to the publication of Maystrenko and Scheck-Wenderoth (2013) with a higher spatial and stratigraphic resolution. The structural model consists of (i) 11 sedimentary units including sea water; (ii) five crystalline crust units composed of four upper crustal units and one lower crustal unit; (iii) one lithospheric mantle unit. The available files include information on the regional variation of these geological units in terms of their depth and thickness, both attributes being allocated to regularly spaced grid nodes with horizontal spacing of 4 km. In comparison, the horizontal spacing of data provided by Maystrenko and Scheck-Wenderoth (2013) was 16 km. Besides, the model provided here resolves Permian, Mesozoic and Cenozoic sediments and Permo-Carboniferous volcanics. The model has originally been developed to analyse the first-order structural features characterizing the crust and the lithospheric mantle below the Central European Basin System and adjacent areas and obtain a basis for numerical simulations of heat transport and to calculate the lithospheric-scale conductive thermal field. Such simulations require the subsurface variation of physical rock properties to be defined, the 3D model differentiates units of contrasting materials, i.e. rock types. On that account, a large number of geological and geophysical data have been analysed (see Related Works) and we shortly describe here how they have been integrated into a consistent 3D model (Methods). For further information on the data usage and the characteristics of the units (e.g., lithology, density, thermal properties), the reader is referred to Maystrenko and Scheck-Wenderoth (2013). The contents and structure of the grid files provided herewith are described in the Technical Information section and the associated data description file (pdf).
This dataset provides the grid files which were used to generate the 3d structural model for Berlin, capital city of Germany. It covers a rectangular area around the political boundaries of Berlin. Geologically the region is located in the Northeast German Basin which is in turn part of the Central European Basin System. The data publication is a compliment to the publications Frick et al., (2019) and Haacke et al., (2019) and resolves 23 geological units. These can be separated into eight Cenozoic, eight Mesozoic and three Paleozoic units, the upper and lower crust as well as the lithospheric mantle. We present files which show the regional variation in depth and thickness of all units in the form of regularly spaced grids where the grid spacing is 100 m. This model was created as part of the ongoing project Geothermal potential Berlin which was also partly situated in Energy Systems 2050, both of whom look at the evaluation of the local thermal field and the closely related geothermal potential. These are obtained by simulating fluid- and heatflow in 3d with numerical models built based on the data presented here. These numerical models and simulations rely heavily on a precise representation of the subsurface distribution of rock properties which are in turn linked to the different geological units. Hence, we integrated all available geological and geophysical data (see related work) into a consistent 3D structural model and will describe shortly how this was carried out (Methods). For further information the reader is referred to Frick et al., (2016) and Frick et al., (2019).
We provide a single file (exodus II format) that contains all results of the modeling efforts of the associated paper. This encompasses all structural information as well as the pore pressure, temperature, and fluid velocity distribution through time. We also supply all files necessary to rerun the simulation, resulting in the aforementioned output file. The model area covers a rectangular area around the Central European Basin System (Maystrenko et al., 2020). The data publication is compeiment to Frick et al., (2021). The file published here is based on the structural model after Maystrenko et al., (2020) which resolves 16 geological units. More details about the structure and how it was derived can be found in Maystrenko et al., (2020). The file presented contains information on the regional variation of the pore pressure, temperature and fluid velocity of the model area in 3D. This information is presented for 364 time steps starting from 43,000 years before present and ending at 310000 years after present. This model was created as part of the ESM project (Advanced Earth System Modelling Capacity; https://www.esm-project.net). This project looks at the development of a flexible framework for the effective coupling of Earth system model components. In this, we focused on the coupling between atmosphere and the subsurface by simulating the response of glacial loading, in terms of thermal and hydraulic forcing, on the hydrodynamics and thermics of the geological subsurface of Central Europe. For this endeavor, we populated the 3D structural model by Maystrenko and Coauthors (2020) with rock physical properties, applied a set of boundary conditions and simulated the transient 3D thermohydraulics of the subsurface. More details about this can be found in the accompanying paper (Frick et al., 2021)
We provide a set of grid files that collectively allow recreating a 3D geological model which covers the Upper Rhine Graben and its adjacent tectonic domains, such as portions of the Swiss Alps, the Molasse Basin, the Black Forest and Vosges Mountains, the Rhenish Massif and the Lower Rhine Graben. The data publication is a complement to the publication of Freymark et al. (2017). Accordingly, the provided structural model consists of (i) 14 sedimentary and volcanic units; (ii) a crystalline crust composed of seven upper crustal units and a lower crustal unit; and (iii) two lithospheric mantle units. The files provided here include information on the regional variation of these geological units in terms of their depth and thickness, both attributes being allocated to regularly spaced grid nodes with horizontal spacing of 1 km. The model has originally been developed to obtain a basis for numerical simulations of heat transport, to calculate the lithospheric-scale conductive thermal field and assess the related geothermal potentials, in particular for the Upper Rhine Graben (a region especially well-suited for geothermal energy exploitation). Since such simulations require the subsurface variation of physical rock properties to be defined, the 3D model differentiates units of contrasting materials, i.e. rock types. On that account, a large number of geological and geophysical data have been analysed (see Related Work) and we shortly describe here how they have been integrated into a consistent 3D model (Methods). For further information on the data usage and the characteristics of the units (e.g., lithology, density, thermal properties), the reader is referred to the original article (Freymark et al., 2017). The contents and structure of the grid files provided herewith are described in the Technical Info section.
This data publication contains mineralogical, geochemical and magnetic susceptibility data of an 87.2 m deep profile of hydrothermally altered plutonic rock in a semi-arid region of the Chilean Coastal Cordillera (Santa Gracia). The profile was recovered during a drilling campaign (March and April 2019) as part of the German Science Foundation (DFG) priority research program SPP-1803 “EarthShape: Earth Surface Shaping by Biota” which aims at understanding weathering of plutonic rock in dependency on different climatic conditions. The goal of the drilling campaign was to recover the entire weathering profile spanning from the surface to the weathering front and to investigate the weathering processes at depth. To this end, we used rock samples obtained by drilling and soil/saprolite samples from a manually dug 2 m deep soil pit next to the borehole. To elucidate the role of iron-bearing minerals for the weathering, we measured the magnetic susceptibility, determined the mineral content and analysed the geochemistry as well as the composition of Fe-bearing minerals (Mössbauer spectroscopy) in selected samples.
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