22 documents found in 398ms
# 1
van Dongen, Renee • Scherler, Dirk • Wittmann, Hella • von Blanckenburg, Friedhelm
Abstract: 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.
# 2
Blanchet, Cécile L.
Abstract: The database presented here contains radiogenic neodymium and strontium isotope ratios measured on both terrestrial and marine sediments. It was compiled to help assessing sediment provenance and transport processes for various time intervals. This can be achieved by either mapping sediment isotopic signature and/or fingerprinting source areas using statistical tools (see supplemental references). The database has been built by incorporating data from the literature and the SedDB database and harmonizing the metadata, especially units and geographical coordinates. The original data were processed in three steps. Firstly, a specific attention has been devoted to provide geographical coordinates to each sample in order to be able to map the data. When available, the original geographical coordinates from the reference (generally DMS coordinates, with different precision standard) were transferred into the decimal degrees system. When coordinates were not provided, an approximate location was derived from available information in the original publication. Secondly, all samples were assigned a set of standardized criteria that help splitting the dataset in specific categories. We defined categories associated with the sample location ("Region", "Sub-region", "Location", which relate to location at continental to city/river scale) or with the sample types (terrestrial samples – “aerosols”, “soil sediments”, “river sediments” - or marine samples –“marine sediment” or “trap sample”). Thirdly, samples were discriminated according to their deposition age, which allowed to compute average values for specific time intervals (see attached table "Age_determination_Sediment_Cores.csv"). The dataset will be updated bi-annually and might be extended to reach a global geographical extent and/or add other type of samples. This dataset contains two csv tables: "Dataset_Nd_Sr_isotopes.csv" and "Age_determination_Sediment_Cores.csv". "Dataset_Nd_Sr_isotopes.csv" contains the assembled dataset of marine and terrestrial Nd and/or Sr concentration and isotopes, together with sorting criteria and geographical locations. "Age_determination_Sediment_Cores.csv" contains all background information concerning the determination of the isotopic signature of specific time intervals (depth interval, number of samples, mean and standard deviation). Column headers are explained in respective metadata comma-separated files. A human readable data description is provided in portable document format, as well. Finally, R code for mapping the data and running statistical analyses is also available for this dataset (see supplemental references).
# 3
Blanchet, Cécile L.
Abstract: The database presented here contains radiogenic neodymium and strontium isotope ratios measured on both terrestrial and marine sediments. It was compiled to help assessing sediment provenance and transport processes for various time intervals. This can be achieved by either mapping sediment isotopic signature and/or fingerprinting source areas using statistical tools (e.g. Blanchet, 2018b, 2018a). The database has been built by incorporating data from the literature and the SedDB database and harmonizing the metadata, especially units and geographical coordinates. The original data were processed in three steps. Firstly, a specific attention has been devoted to provide geographical coordinates to each sample in order to be able to map the data. When available, the original geographical coordinates from the reference (generally DMS coordinates, with different precision standard) were transferred into the decimal degrees system. When coordinates were not provided, an approximate location was derived from available information in the original publication. Secondly, all samples were assigned a set of standardized criteria that help splitting the dataset in specific categories. We defined categories associated with the sample location ("Region", "Sub-region", "Location", which relate to location at continental to city/river scale) or with the sample types (terrestrial samples – “aerosols”, “soil sediments”, “river sediments”, “rocks” - or marine samples –“marine sediment” or “trap sample”). Thirdly, samples were discriminated according to their deposition age, which allowed to compute average values for specific time intervals (see attached table "Age_determination_Sediment_Cores_V2.txt"). A first version of the database was published in September 2018 and presented data for the African sector. A second version was published in April 2019, in which the dataset has been extended to reach a global extent. The dataset will be further updated bi-annually to increase the geographical resolution and/or add other type of samples. This dataset consists of two tab separated tables: "Dataset_Nd_Sr_isotopes_V2.txt" and "Age_determination_Sediment_Cores_V2.txt". "Dataset_Nd_Sr_isotopes_V2.txt" contains the assembled dataset of marine and terrestrial Nd and/or Sr concentration and isotopes, together with sorting criteria and geographical locations. "Age_determination_Sediment_Cores_V2.txt" contains all background information concerning the determination of the isotopic signature of specific time intervals (depth interval, number of samples, mean and standard deviation). Column headers are explained in respective metadata comma-separated files. A full reference list is provided in the file “References_Database_Nd_Sr_isotopes_V2.rtf”. Finally, R code for mapping the data and running statistical analyses is also available for this dataset (Blanchet, 2018b, 2018a).
# 4
Albert, Francisca
Abstract: This data set includes movies and images of sandbox experiments aiming at understainding the process of subduction erosion at active plate margins (Albert, 2013). Four experiments are documented by means of movies showing the evolution of a strong wedge (sand-sugar mix, “Reference experiment.avi”), a weak wedge (sand only, “F1 experiment.avi”) and two successive phases of a wedge that undergoes subduction erosion by subducting topographic highs (first stage without subducting topography= “HL.1 experiment.avi” and second stage with subducting topography = “HL.2 experiment.avi”). Images of preliminary tests and experiments not considered in Albert (2013) are given in “Appendix A2.2.pdf” (small box experiments) and “Appendix A3.3.pdf” (experiments varying friction and slope).
# 5
Pittore, Massimiliano • Ozturk, Ugur • Moldobekov, Bolot • Saponaro, Annamaria
Abstract: The EMCA landslide catalog of Central Asia covers mostly western and northern Kyrgyzstan as well as Tajikistan's Region of Republican Subordination. The catalog is a summary (point locations) of the documented landslides between 1954 and 2009, which are collected by the Central Asian Institute for Applied Geosciences through geological surveys (field campaigns) on single sites close to urban areas in order to mitigate landslide risk. The catalog is presented in identical .csv and NetCDF (.nc) formats. Both the formats include the point locations of the landslides (variables: latitude [WGS 84], longitude [WGS 84]), and the dates of about 5% of the landslides (variable: date). The remaining %95 of the data is undated and marked as NaT (dating not possible). These documented landslides mostly happened on soft and semi-hard rock layers within the areas made of Mesozoic-Cenozoic formations: these formation are represented mainly by layers of clays, argillites, siltstones, sandstones, marls, limestone, gypsum and conglomerates, which are mostly covered by Quaternary loess deposits (Kalmetieva et al., 2009, p.75). The EMCA landslide catalog is far from being a complete datasets for the entire region, since majority of the area is inaccessible or hard to reach due to mountainous relief, which in turn decreases the chance of collecting information about ancient as well as modern landslides through field campaigns.
# 6
Schuessler, Jan A. • von Blanckenburg, Friedhelm • Bouchez, Julien • Hewawasam, Tilak • Uhlig, David
Abstract: The dataset contains chemical analyses from the well-characterised Hakgala field site in the tropical Highlands of Sri Lanka. This site is located on a road cut between Nuwara Elia and Welimada (06.92923° N, 80.81834° E, 1753 m altitude), bordering a 12 km^2 natural forest reserve consisting of pristine, mature, stable upper montane rain forest, close to the Hakgala Botanical Garden. A deeply weathered regolith depth profile (ca. 10 m) developed on a hillslope underlain by charnockite bedrock. Adjacent to the regolith profile ecologically pristine catchments (>1 km^2) are drained by small creeks. Here, data on samples of all compartments of the Critical Zone (defined as the near surface layer of the Earth extending from the bottom of the weathering zone to the top of the tree canopy) are reported. The dataset compiles published (Hewawasam et al., 2013, GCA, 118, 202-230) and new data (Schuessler et al., 2018, Chemical Geology) of element concentrations, stable Mg isotopes, and radiogenic Sr isotope ratios on stream water (time series sampling 2010-2013), vegetation, soil, saprolite (depth profile sampling), weathered bedrock (corestones), and unweathered bedrock. From this data, weathering indicators such as the chemical depletion fraction (CDF) and the element mass transfer coefficients (Tau) were calculated and reported in the dataset. The samples used for these analyses have been assigned with International Geo Sample Numbers (IGSN, www.igsn.org). Details on sampling locations are provided via IGSN links in the tables and in the related work section on the DOI Landing Page at GFZ Data Services. Moreover, the IGSN data can be accessed by adding the IGSN after igsn.org, e.g. igsn.org/GFFB1003V. Further details on sampling and locations are provided in Hewawasam et al. (2013, GCA, 118, 202-230). This publication contains an annotated summary table serving as a supplementary table for Schuessler et al. (2018, Chemical Geology) in pdf and xlsx (Microsoft Excel) formats. In addition, separate tables reflecting differing samples and methodologies for input into statistical software are provided as comma separated files. Column headers for all tables are explained in a separate csv file (Data columns headers for tables S1 to S3.csv). The analytical methodologies used to generate the data are described in the data description file.
# 7
Dietze, Michael
Abstract: Environmental seismoloy is a scientific field that studies the seismic signals, emitted by Earth surface processes. This R package eseis provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history. eseis contains a growing set of function to handle the complete workflow of environmental seismology, i.e., the scientific field that studies the seismic signals that are emitted by Earth surface processes. The package supports reading the two most common seismic data formats, general functions for preparational and analytical signal processing aswell as specified functions for handling signals generated by Earth surface processes. Finally, graphical plot functions are provided, too. The software package contains 51 functions and two example data sets (eseis-supplementary_material.zip). It makes use of a series of dependency packages described in the DESCRIPTION file of the package.
# 8
Darmawan, Herlan • Walter, Thomas • Richter, Nicole • Nikkoo, Mehdi
Abstract: This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006). The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South). TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz. The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud. The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017). Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud. The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software.
# 9
Uhlig, David • Schuessler, Jan A. • Bouchez, Julien • Dixon, Jean L. • von Blanckenburg, Friedhelm
Abstract: This dataset is a supplementary dataset to the manuscript: “Uhlig, D., Schuessler, J. A., Bouchez, J. L., Dixon, J., and von Blanckenburg, F.: Quantifying nutrient uptake as driver of rock weathering in forest ecosystems by magnesium stable isotopes, Biogeosciences, 2017“. The dataset contains physicochemical parameters of stream water (pH, temperature, conductivity discharge, alkalinity) , and chemical and Mg isotope analyses of stream water, vegetation, soil, saprolite, weathered bedrock and unweathered bedrock of three headwater catchments at Providence Creek in the Southern Sierra Nevada, California, USA. Further, the dataset contains soil and saprolite weathering indicators such as the chemical depletion fraction (CDF) and mass transfer coefficients, as well as elemental regolith production fluxes, elemental net solubilisation fluxes, elemental dissolved river fluxes, elemental litterfall fluxes, nutrient recycling fluxes and elemental dissolved export efficiencies that rely on measured data reported in the above study and data from literature. These data and metrics were used to track the pathway of Mg and other nutrients through the headwater catchments at the Critical Zone Observatory of the Southern Sierra Nevada.
# 10
Richter, Nicole • Nikkhoo, Mehdi • de Zeeuw-van Dalfsen, Elske • Walter, Thomas. R.
Abstract: The datasets included in this data publication are: (1) the TLS combined point cloud (consisting of ∼15 million data points), (2) a Digital Elevation Model (DEM) with 1 m pixel spacing which was generated from (1), and (3) a shaded relief of (2) in kmz format. These datasets are supplement to de Zeeuw-van Dalfsen et al. (2017), who used them to study structural and geomorphological features at the nested summit craters of Láscar Volcano, Chile. However, in the paper the data were used in a local reference frame while we here provide both the TLS point cloud and the DEM product in global coordinates (WGS 1984 UTM Zone 19 South). Light detection and ranging (LiDAR) is a technique where a laser pulse is actively emitted from a LiDAR instrument and the echo that returns from a target object is recorded. The distances between the instrument and the target points are calculated from the round-trip travel time of the laser pulse (Fornaciai et al., 2010). A terrestrial laser scanner (TLS) uses this technique in a scanning mode where the laser beam is deflected into different directions by an oscillating mirror while at the same time the scanner’s head is rotating. We used a long-range RIEGL LMS-Z620 instrument with a field of view of up to 80° by 360° in the vertical and horizontal plane, respectively. The maximum repeatability of this instrument is 5 mm, but this value increases with increasing distance between the scanner and the target, when viewing geometries or the target reflectivity are not optimal or when atmospheric conditions vary and are not ideal. From the acquired 3D point cloud topographic details can be retrieved over a maximum distance of 2 km. However, newer instruments can reach distances of 6 km or more.
Georeferencing (local coordinate system) In total, four TLS scans were acquired on two days in November 2013 (two at each day to overcome shadowing effects). The two point clouds from each view point were combined using tie points, i.e. reflectors that were placed in the field, and the RiSCAN Pro Software (http://www.riegl.com). For the two point clouds from day 1, we achieved a standard deviation of 0.0023 m using 6 tie points, while for the two point clouds acquired on day 2 we reached a standard deviation of 0.0052 m using 3 tie points. In addition to the TLS measurement, the reflectors’ positions were also measured using a total station. This additional data allowed us to 1) orientate each of the two point clouds to a local geodetic reference frame in the XY plane using a 3D affine transformation with a remaining RMSE of ∼1 cm and 2) estimate the orientation about Z and the full translation parameters using hand-held GPS coordinates of a common point and the individual tie points. Following this procedure we produced a combined point cloud of all four TLS scans in a local geodetic reference frame. Georeferencing (global coordinate system) In order to derive the coordinates of the TLS point cloud in a global coordinate system, we used the open-source software Minuit2 5.18/00 which was developed at CERN (James and Winkler, 2004 and references therein). This tool finds the minimum value of multi-parameter functions and was in our case employed to find the minimum root mean square residuals (in elevation) between the TLS point clouds and a reference DEM featuring a 1 m pixel spacing that was calculated from tri-stereo optical Pléiades-1 satellite imagery. When applying this minimization technique, the data are transferred to the same coordinate system as the reference data (WGS 1984 UTM Zone 19 South). In a first step, we minimized the two TLS point clouds from the two different acquisition dates separately. We masked out areas from the Pléiades reference DEM that we know are very different when compared to the TLS point data. For instance, areas along the steep crater walls are interpolated to a high degree in the Pléiades DEM, while the scanner-facing crater walls are expected to have comparably precise point values in the TLS dataset. Thereafter, we combined the TLS point clouds and ran another Minuit RMSE minimization onto the masked Pléiades DEM.
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