Other language confidence: 0.9701576392344721
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.
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.
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).
Climatically formed alluvial river-terrace sequences offer an exceptional opportunity to study valley-width evolution under similar discharge and lithologic conditions. To investigate additional parameters controlling valley width, we globally compiled alluvial-terrace sequences that have been associated with late Quaternary climate changes. All terrace cross-sections that are accepted to our compilation (1) include both valley sides, (2) show absolute values of distance and height, as well as profile location, and, (3) display a minimum of three terrace levels out of which at least one is preserved as a paired terrace. The terrace width and height measurements are summarized in this dataset. The data are presented as Excel and ASCII tables.
A quantification of bedrock erodibility under fluvial impact erosion is required for various tasks in geomorphology, landscape evolution, and hydraulic engineering. However, it is challenging to measure in the field. Various proxy methods for easy measurement have been suggested and applied, but none of these has been benchmarked against high-quality data from the laboratory or field. We have collected field and laboratory data on erodibility using erosion mills as well as proxy data from the Schmidt hammer, Mohs' hardness, and the Annandale and Selby methods for 18 different lithological units.
To investigate geotechnical controls on erodibility of rocks in fluvial impact erosion, we raised a par-allel dataset of i) rock erodibility, using purpose designed erosion mills (Turowski et al., 2023a) including grain size distributions for the eroded material, and ii) rock properties such as compressive strength, indirect tensile strength, Young’s modulus, and Poisson’s ratio. In addition, we measured proxies for geotechnical parameters, including the Schmidt hammer rebound value, Mohs’ hardness, bulk density, and ultrasonic pulse velocities. Samples were obtained with a water-cooled, 200 mm diamond core bit in Switzerland and southern Germany, either from in-situ bedrock or boulders. In total, 18 lithological units were sampled. For some units, we obtained several cores either to increase the usable length or the quality, or to sample local variations in lithological properties (e.g., the dominant grain size) or geometry (e.g., the core orientation with respect to bedding planes). Back in the workshop, cores were cut into discs of either ~5.5 cm or ~12 cm length, for erosion and geotechnical experiments, respectively, and further prepared depending on the needs for the specific measurement.
VERSION HISTORY:-On October 18, 2018 we republished all simulation data for all water (global) sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.- On November 27, 2018 we republished simulation data for monthly variables swe, soilmoist and rootmoist for impact model PCR-GLOBWB due to an error in the units. Instead of reporting mass per area (kg/m2), values corresponded to mass flux rate (kg/m2/s). Values were thus multiplied by 86400 in order to obtain the correct values in kg/m2. This data caveat was documented in the ISIMIP website (ISIMIP2a: PCR-GLOBWB reported three variables in wrong unit).----------------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/. For accessing the data set as in http://doi.org/10.5880/PIK.2017.010 before November 27, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.de.----------------------------------------------------------------------------DATA DESCRIPTION:The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2
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
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2.
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. The Nahal (river) Eshtemoa is a gravel-bed river draining 119 km² of the Southern Hebron Mountains and the Northern Negev, northeast of Beer Sheva, Israel. The climate in the catchment is semi-arid, with a mean annual precipitation of 286 mm. Rainfall mainly occurs between October and May. The river is ephemeral with flash floods occurring on average five times per year (Alexandrov et al., 2009). The recurrence interval of the bankful discharge of 26 m3 s-1 has been estimated to be 1.25 years (Powell et al., 2012). Bedload fluxes are high by worldwide standards with sediment transport as much as 400 times more efficient than in a typical perennial humid river (Laronne and Reid, 1993; Reid and Laronne, 1995). The river is equipped with a monitoring station in a straight channel section with a trapezoidal cross section. The banks are nearly vertical, 1.2 m high, and comprise aeolian fines and interbedded gravel. The mean channel slope is 0.0075, which is generally mirrored by the water surface slope, with exception during the arrival of a flashflood bore (Meirovich et al., 1998). The data presented here are for the flood of the 22nd February 2016.They show a high bedload flux with peaks exceeding 1 kg/sm and water level between 0.5 and 0.8 m. The event has been previously described by Dietze et al. (2019). The data were used to assess the quality of a physical model (Tsai et al. 2012) predicting the seismic spectrum generated by the impact of bedload particles moving along the channel bed. The model requires knowledge on stream and sediment characteristics to constrain the source terms, e.g., the channel geometry and grain size distribution, as well as ground properties affecting the wave propagation, i.e., frequency-dependent wave velocity or attenuation characteristics. The complementary controlled source and passive seismological data are published in a separate data publication (Lagarde et al., 2020).
| Organisation | Count |
|---|---|
| Wissenschaft | 13 |
| Type | Count |
|---|---|
| unbekannt | 13 |
| License | Count |
|---|---|
| offen | 13 |
| Language | Count |
|---|---|
| Englisch | 13 |
| Resource type | Count |
|---|---|
| Keine | 13 |
| Topic | Count |
|---|---|
| Boden | 10 |
| Lebewesen und Lebensräume | 12 |
| Luft | 9 |
| Mensch und Umwelt | 13 |
| Wasser | 10 |
| Weitere | 13 |