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Granulometry of fluvial sediment from the Gersprenz, Modau, Muemling, and Upper Neckar rivers, Germany

Mixing modeling results of fluvial sediment from the Gersprenz, Modau, Muemling, and Upper Neckar rivers, Germany

Geochemistry of fluvial sediment from the Gersprenz, Modau, Muemling, and Upper Neckar rivers, Germany

Granulometry, geochemistry and mineralogy of fluvial sediment from the Gersprenz, Modau, Muemling, and Upper Neckar rivers, Germany

This dataset accompanies the manuscript entitled "Temporal and Granulometric Variability of Fluvial Sand Composition: An Annual Time Series from Four Rivers in SW Germany" by Laura Stutenbecker et al., submitted to JGR Earth Surface in March 2023. The study aims at analyzing the temporal variability of fluvial sediment composition. For this purpose, sediment of four rivers was sampled monthly over the course of one year between April 2019 and December 2020 at the same locations, using the same operator, tools, and sampling strategy, resulting in a total of 46 grab samples. The sampled rivers were the Gersprenz, Modau, Mümling and Upper Neckar rivers in southwestern Germany. The summary of sample names, coordinates, and sampling dates can be found in the data table "Sampling dates". The sediment was wet-sieved for grain-size analysis using six sieve sizes (63, 125, 250, 500, 1000, and 2000 micrometers). The percentage of each fraction after drying and weighing is provided in the table "Granulometry". The individual fractions (172 sub-samples in total) were analyzed for chemical composition. Geochemical analysis was performed using wavelength-dispersive X-ray spectrometry on pressed powder pellets using a S8 Tiger 4 kW (Bruker) spectrometer at Technical University of Darmstadt. Geochemical data of major element oxides and selected trace elements (in wt% and ppm, respectively) is provided in data table "XRF". Mineralogical analysis was performed on selected samples using X-ray diffraction on powdered samples using a Panalytical X'Pert Pro diffractometer at Goethe University Frankfurt am Main. The percentages of the minerals quartz, alkali feldspar, plagioclase, calcite, dolomite, illite/muscovite, kaolinite, chlorite, amphibole, goethite, and hematite are provided in data table "XRD". The data was input into an unmixing model following Lizaga et al. (2020, https://doi.org/10.1007/s11269-020-02650-0). The data table "Mixing modeling results" sums up the model performance (goodness of fit) as well as the modeled sediment source contributions (in percent, mean and standard deviation) of three considered sediment sources from the literature.

Mineralogy of fluvial sediment from the Gersprenz, Modau, Muemling, and Upper Neckar rivers, Germany

Grain-size analysis obtained from sediment core BT03 (Eiderstedt peninsula; south-eastern North Sea)

Core BT03 originates from a reinstated, former managed marsh (Eiderstedt peninsula). The marsh in Eiderstedt is exposed to storm waves from the open North Sea. Grain-size data were used to determine and quantify multiple sedimentary processes by the application of end-member modelling.

Grain-size analysis obtained from sediment core BT02 (Eiderstedt peninsula; south-eastern North Sea)

Core BT02 originates from a reinstated, former managed marsh (Eiderstedt peninsula). The marsh in Eiderstedt is exposed to storm waves from the open North Sea. Grain-size data were used to determine and quantify multiple sedimentary processes by the application of end-member modelling.

Grain-size analysis obtained from sediment core RD04 (island of Sylt)

Core RD04 originates from a natural back-barrier marsh (island of Sylt). The marsh in Sylt is a low-energy, back-barrier marsh. Grain-size data were used to determine and quantify multiple sedimentary processes by the application of end-member modelling.

Grainsize analysis and radionuclide measurements (210Pb, 137Cs, 226Ra) obtained from sediment cores RD04 (island of Sylt), BT02 and BT03 (Eiderstedt peninsula; south-eastern North Sea)

Three sediment cores were retrieved from marshes at the southern North Sea coast, recovering the past 100 years. Core RD04 originates from a natural back-barrier marsh (island of Sylt); cores BT02 and BT03 from a reinstated, former managed marsh (Eiderstedt peninsula). Whereas the marsh in Sylt is a low-energy, back-barrier marsh, the marsh in Eiderstedt is exposed to storm waves from the open North Sea. The study provides a characterisation of the sedimentary processes that control vertical salt marsh growth in different energetic settings. Data include grain-size analysis and radionuclide activity of 137-Cs, 210-Pb and 226-Ra. Measurements of the radionuclides were used to determine sediment accretion rates. Grain-size data were used to determine and quantify multiple sedimentary processes by the application of end-member modelling.

PebbleCounts: a Python grain-sizing algorithm for gravel-bed river imagery

Grain-size distributions and their associated percentiles are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are typically achievable only at the patch (1 square meter) scale. With the advent of unmanned aerial vehicle systems and increasingly high-resolution cameras, we can now generate orthoimagery over large areas at resolutions of <1 cm. These scales, along with the complexity of many natural environments in high-mountain rivers, necessitate different approaches for photo sieving. Here, a new open-source algorithm is presented: PebbleCounts. As opposed to other image segmentation methods that use a watershed approach and automatically segment entire images, PebbleCounts relies on k-means clustering in the spatial and spectral (color) domain and rapid manual selection of well-outlined grains. This results in improved estimates for complex river-bed imagery without the need for post-processing.

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