Other language confidence: 0.983669178329061
Here we provide in situ 10Be data, meteoric 10Be data, X-Ray fluorescence data, infiltration rate field date, chemical extraction data, a summary of grain size data, all grain size data (Table S7), mineral point counting data, XRD data, soil grain size data, and data from laboratory measurements of hydrological parameters. Field work in Santa Gracia was conducted in February of the years 2019 and 2020 and laboratory work was conducted between 2019 and 2023. This data publication accompanies our study (Lodes et al., 2024), in which we investigate whether lithology controls drainage density in Santa Gracia, a semi-arid field site in Central Chile. In the study, we compare the density of drainages in two distinct, neighbouring landscapes underlain by a monzogranite and two diorite plutons (which we refer to as the “inner diorite” and the “outer diorite”). We collected multiple datasets to understand the underlying mechanisms behind the drainage density differences. The data was collected as part of the German Science Foundation (DFG) priority research program SPP-1803 “EarthShape: Earth Surface Shaping by Biota” (grant SCHE 1676/4-1 and -2 to D. S.; funding of P. G. through grant BE 1780/53-1 and -2).
This data publication contains a high resolution molecular dataset of a study aiming to trace variations in organic carbon sourcing along the Kali Gandaki River in Central Nepal. The data are on samples from different materials in the landscape (litter, soil, bedrock) and river sediments. On these samples we measured the extractable lipid fraction by measured by negative electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). The data was generated between 2015-05 and 2017-12. Please consult the associated data description and Menges et al. (2020) for more details.
We present a new Python-based Jupyter Notebook that helps interpreting detrital tracer thermochronometry datasets and quantifying the statistical confidence of such analysis. Users are referred to the linked GitHub repository for usage and methods. https://github.com/mdlndr/ESD_thermotrace
This data publication contains the data sets of a study aiming to trace variations in organic carbon sourcing along the Kali Gandaki River in Central Nepal. The data are on samples from different materials in the landscape (litter, soil, bedrock) and river sediments. On these samples we measured total organic carbon content, stable carbon and nitrogen isotopes, radiocarbon content and surface area. The data was generated between 2015-05 and 2017-12. The tabular data are provided as csv and Excel verisons.
In the arid and largely abiotic region of northern Chile the environmental conditions are favorable for measurement of the tectonic and climate influence on catchment denudation rates. Previous studies of denudation rates from cosmogenic 10Be and 26Al concentrations are limited to single drainages. In this study, we present 34 new 10Be and eight 26Al derived catchment-averaged denudation rates from 33 catchments to analyze variations of denudation rates between 18°S to 23°S in the Coastal and Western Cordilleras of northern Chile. Cosmogenic nuclide-derived denudation rates range from 0.4±0.5 to 20.6±1.5 m/Myr in the Coastal Cordillera and from 1.4±0.7 to 168.0±19.8 m/Myr in the Western Cordillera. The controls on the denudation rates are evaluated using a statistical factor analysis of ten selected catchment parameters. Denudation rates indicate a strong linear relationship with channel steepness indices but insignificant correlations and covariation with mean annual precipitation rates, drainage area, stream order, mean elevation, mean local relief, mean basin slope and analyzed grain size. Thus, denudation rates are better correlated with tectonic controls at catchment scale than orogen-scale plate tectonics in the Western Cordillera and Coastal Cordillera. These data are supplementary material to Starke et al. (2017). For further information about methods used and parameters provided, please also see the README. (1) as Microsoft Excel file: Starke-et-al-2017-JGR-Supplementary-Tables.xlsx (2) as comma separated text files (.csv) in a zip folder: Starke-et-al-2017-JGR-Supplementary-Tables.zip) (3) as printable pdf: Starke-et-al-2017-JGR-Supplementary-Tables.pdf.
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