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27 results for “Bedload”
Annual bedload accumulation from sediment basin surveys in small gauged watersheds in the Andrews Experimental Forest, 1957 to present
Sediment debris basins are established within the Andrews Experimental Forest as part of paired watershed experiments examining differences in streamflow and nutrient chemistry due to timber harvest. Basins are constructed below the stream gaging station in each of five basins, and these basins and the deposits of sediment within them are re-surveyed or emptied annually to measure bedload sediment production. Basins are measured on Watersheds 1, 2 (control) and 3 beginning with wateryear 1957 and on Watersheds 9 (control) and 10 beginning wateryear 1974. Data collection is ongoing at an annual time step. Data provided include the watershed name, wateryear, survey method, watershed area, annual bedload volume and accumulation rate. These data display both the chronic production of sediment, as well as pulsed, episodic bedload from landslides within the contributing basins.
Stream discharge and bedload accumulation in gauged watersheds at the South Umpqua Experimental Forest, Coyote Creek, 1963 to 1981 and 2001 to present
Stream discharge is collected on four small watersheds in the Coyote Creek drainage within the South Umpqua Experimental forest in the southwest Oregon Cascades. Stream discharge data was started in October 1963 and discontinued in June 1981 (discontinued April 1985 on Watershed 4). Stream discharge measurement was resumed in December 2000 on all four watersheds. Watersheds 1, 2, and 3 were harvested with differing silvicultural methods in summer 1971, and watershed 4 is the control. High resolution temporal data is provided as well as daily, monthly and annual summary data. Streamflow data by sampling intervals are also provided from 1970 to 1981 when stream water chemistry data were being collected. Annual bedload accumulation totals from each of the four watersheds is also provided beginning 2001.
Development of a machine learning model for river bedload - Data, Model, and Scripts
<p>This repository for “Development of a machine learning model for river bedload” Hosseiny et. Al (in review at Earth Surface Dynamics) contains the following assets. These assets may need to be modified for your purposes. You are responsible for inspecting these assets and making adjustments as necessary.</p> <p>Assets:</p> <p>1) The trained ANN model described in Hosseiny et al. (in review) as a .zip file named ‘Hosseiny_et_al_trained_ANN.zip’. This contains a folder (BEDLOAD_MODEL_FINAL) which contains the trained ANN Model (saved_model.pb) and associated information related to the input variables and variable weights.</p> <p>2) An accompanying Jupyter notebook named “bedload_ann_example.ipynb” that provides a step-by-step guide for implemented the trained ANN model (Asset 1).</p> <p>3) A .xls file named “Hosseiny et al_Supplemental_Data_Tables.xlsx” which provides the original observations that the model was trained and tested on, the summary statistics of the original input data as a compilation and for individual sites, the model errors associated with training and validation steps, the bedload calculations from the four uncalibrated existing bedload transport models described in the original study and for the ANN for the test data population, associated summary statistics with model output, and additional site-specific calculations of model error.</p>
Bedload data (deposition from overland flow) measured at the three Conmod Pilot study locations at Jornada Basin LTER, 2008-2010
This data package contains measurements of bedload samples (suspended particles) collected during overland flow events in the Connectivity Modifier (Conmod) Pilot study on the Jornada Experimental Range from 2008-2010. There were 3 sites for this study: Gravelly Ridges, Aeolian, and Dona Ana. Within each site, there were 8 study plots, 4 of which were treatment plots where connectivity modules (conmods) were installed to decrease gap sizes between perennial vegetation. The plots were 8 x 8 meters and had an 8 x 8 meter buffer zone on both sides of the plot (upwind and downwind). To collect water from overland flow events, four to six belowground catchment containers were installed in upslope and downslope buffer zones at each study plots. Bedload containers were monitored monthly 2008, 2009, and 2010. Bedload material collected by the containers during overland flow events was weighed and analyzed for organic matter content by the loss on ignition method. This study is complete and was the pilot study to the newer Cross Scale Interactions Study.
DEM simulations of size-segregation during bedload transport
<p>This depository contains the data of all DEM simulations used in the publication Chassagne, R., Maurin, R., Chauchat, J., Gray, J., & Frey, P. (2020). Discrete and continuum modelling of grain size segregation during bedload transport. <em>Journal of Fluid Mechanics,</em> <em>895</em>, A30. doi:10.1017/jfm.2020.274, as well as post processing scripts to use the data.</p> <p>The simulations are located in two folders, fine/ (simulations for which the amount of fine particles is varied) and sizeRatio (simulations for which the size ratio between large and small particles is varied). The data of each simulations are contained in separate subfolders named after the simulation. For example, Fine2R1.5/ corresponds to a simulation with 2 layers of small particles and a size ratio of 1.5. For each simulation, the time data are saved in data.hdf5 and averaged data in average.hdf5. A GeomParam.txt file is also in each folder. It contains information of the simulation that the post processing programm will read. The python script used to initiate the YADE-DEM simulation is also given for information (it contains all parameters of the simulation).</p> <p>The post-processing program has been coded in python2.7 with an oriented-object procedure. The h5py package is necessary to read the .hdf5 files. The scripts do not work in python3, but can be very easily adapted if necessary (you only have to modify the "print" functions). The scripts are available in ScriptsPP/ and are organized as follow. A mother class in SegregationPP and two child classes SegFull (to load the full time data set) and SegMean (to load only average data). A script examplePP.py is proposed and shows how to manipulate theses classes and the data.</p>
DEM simulations of bi-disperse beds during bedload transport
<p>This depository contains the data of all DEM simulations used in the publication Chassagne, R., Frey, P., Maurin, R., and Chauchat, J. Mobility of bidisperse mixtures during bedload transport. Physical Review Fluids, 5(11):114307. doi:10.1103/PhysRevFluids.5.114307, as well as post processing scripts to use the data.</p> <p>The simulations are located in seven folders, Monodisperse/ (mondisperse simulations where the fluid forcing is varied), N0.5/ (simulations with 0.5 layer of large particles above a small particle bed and or different fluid forcing), N1/ (simulations with 1 layer of large particles above a small particle bed and or different fluid forcing), N2/, N3/, N4/ and sizeRatio (2 layers of large particles, fixed fluid forcing but the diameter of the underlying small particles is varied). The data of each simulations are contained in separate subfolders named after the simulation. For example, H8Sh0.45/ corresponds to a monodisperse simulation with a bedheight of 8dl (dl is the large particle diameter) and a shields number of 0.45. H10N2R2Sh0.7/ corresponds to a bidisperse simulation with a bed height of 10dl, 2 layers of large particles, a size ratio of 2 between large and small particles and a shields number of 0.7. For each simulation, the time data are saved in data.hdf5 and averaged data in average.hdf5. A GeomParam.txt file is also in each folder. It contains information of the simulation that the post processing programm will read.</p> <p>The python script used to initiate the YADE-DEM simulation is also given for information (it contains all parameters of the simulation). The post-processing programm has been coded in python2.7 with an oriented-object procedure. The h5py package is necessary to read the .hdf5 files. The scripts do not work in python3, but can be very easily adapted if necessary (you only have to modify the "print" functions). The scripts are available in ScriptsPP/ and are organized as follow. For bidisperse simualtions, a mother class in SegregationPP and two child classes SegFull (to load the full time data set) and SegMean (to load only average data). For monodisperse simualtions, a mother class in MonodispersePP and two child classes MonoFull (to load the full time data set) and MonoMean (to load only average data). Two scripts examplePP1.py and examplePP2.py are proposed and show how to manipulate theses classes and the data.</p>
Experimental data of geoplate bedload signal of single pebbles
<p>Geophone raw data acquired during experiments carried out in the Hydraulics Laboratory of the Department of Civil, Environmental and Mechanical Engineering, University of Trento, Italy in dry and flow conditions.</p> <p>Experiments in dry conditions used a metal sphere hitting different locations on the plate. Signal was sampled with two different acquisition rates (10 and 30 kHz)</p> <p>Experiments in water flow conditions used 17 pebbles of different size and shape and 5 different flow conditions (F1 to F5).</p> <p>File "Metadata.txt" reports more information on how to read and use the dataset.</p> <p>These data have been used in the publication "Analysis of the vibration modes of impact geoplates and implications for bedload flux and grainsize measurements" by Portogallo et al., submitted to Water Resources Research.</p>
An experimental dataset to explore the size ratio impact on an intruder segregating in bedload transport
<p>This repository gathers :</p> <ul> <li>The treated data used in the article "Exploring the size ratio impact on an intruder segregating in bedload transport" from Dedieu B., Rousseau H., Frey P. and Chauchat J. in Physical Review of Fluids (DOI: <a href="https://doi.org/10.1103/PhysRevFluids.9.104302" target="_blank" rel="noopener">10.1103/PhysRevFluids.9.104302</a>),</li> <li>Some re-computed data from the experiments of <a href="https://doi.org/10.1103/PhysRevFluids.7.064305" target="_blank" rel="noopener">Rousseau H. et al.(2022)</a> in csv format,</li> <li>A python3 package <em>codes</em> used to load the data.</li> </ul> <p>Explanations on how to use the codes and how the data are organized can be found in the <em>README.md</em>.</p> <p>Feel free to contact the authors if you need more information or wish to access the raw image data.</p>
Bedload rate time series
<p><strong>Files R1qsraw.txt to R7qsraw.txt</strong>: Bedload rate (g/s) time series for total bedload (column 1) and 14 grain size fractions over seven experimental runs (R1 to R7). Fractional bedload rates go from column 2 to 15 as follows: <br> 0.5-0.7 mm (column 2)<br> 0.7-1 mm (column 3)<br> 1-1.4 mm (column 4)<br> 1.4-2 mm (column 5)<br> 2-2.8 mm (column 6)<br> 2.8-4 mm (column 7)<br> 4-5.6 mm (column 8)<br> 5.6-8 mm (column 9)<br> 8-11 mm (column 10)<br> 11-16 mm (column 11)<br> 16-22 mm (column 12)<br> 22-32 mm (column 13)<br> 32-45 mm (column 14)<br> 45-64 mm (column 15)</p> <p><strong>File SurfaceDg.txt</strong>: Contains the geometric mean size for the bed surface in mm (column 2) for different experimental times (time in h, column 1)</p> <p><strong>File BedloadDg.txt</strong>: Contains the geometric mean size for the bedload in mm (column 2) every 1 h (time in h, column 1)</p> <p><strong>File slope.txt: </strong>Contains the bed slope at the thalweg in m/m (column 2) for different experimental times (time in h, column 1)</p> <p> </p>
Bead tracking experimental ground truth for studying size segregation in bedload sediment transport
<p>Video sequences to study size segregation in bedload transport were recorded. Experiments consisted in mixtures of two-size spherical glass beads entrained by a turbulent supercritical free surface water flow over a mobile bed. The aim is to track all beads over time to obtain trajectories, particle velocities and concentrations, for studying bedload granular rheology, size segregation and associated morphology.</p> <p>This upload consists in :</p> <ul> <li>a 1000-frame experimental image sequence recorded at 130 fps with approximately 400 beads per frame (about 300 coarse and 100 small beads). The image resolution is 1280x320;</li> <li>the ground truth in the directory \result . It was obtained based on a tracking algorithm with subsequent expert modification. The tracking algorithm was developed by H. Lafaye de Micheaux et al. The code implementing the tracking algorithm is available on <a href="https://github.com/hugolafaye/BeadTracking">https://github.com/hugolafaye/BeadTracking</a>. The ground truth is a '.mat' file containing in particular the variable 'trackData' being a cell array of tracking matrices. There is one tracking matrix for each image of the sequence. Complete information on data format is given in the file readme.txt in the github BeadTracking package.</li> <li>In addition it contains three files allowing the user to run the BeadTracking package specifically on the experimental sequence : <ul> <li>sequence_param.txt : parameter file</li> <li>sequence_base_mask.tif : to remove the base</li> <li>template_transparent_bead_rOut10_rIn6.mat : a template for bead detection</li> </ul> </li> </ul>
Experiments on Grain Size Segregation in Bedload Transport on a steep Slope
<p>This dataset is the basis of the publication:</p> <p>Frey, P., Lafaye de Micheaux, H., Bel, C., Maurin, R., Rorsman, K., Martin, T., Ducottet, C., 2020. Experiments on grain size segregation in bedload transport on a steep slope. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2019.103478.</p> <p>Experiments consisted in bedload of two-size spherical glass beads transported at equilibrium by a turbulent supercritical free surface water flow over a mobile bed. Two runs, one with a low rate of large black beads (S6), the other with a higher rate (S20), are considered. This dataset consists in:</p> <p>- temporal sequences of uncompressed tif images corresponding to figure 5 showing small particle concentration : 9 sequences for run S6 (BillesBaumerMicro) and 9 sequences for run S20 (BillesbaumerAmontSequence)</p> <p>- two ‘.mat’ file corresponding to runs S6 (trackData_Micro_S6.mat) and S20 (trackData_Amont_S20.mat) giving all the trajectories of all beads.</p> <p>Trajectories were obtained with a tracking algorithm developed by H. Lafaye de Micheaux et al. (2016,2018) building on Hergault et al. (2010). The code implementing the tracking algorithm is available on <a href="https://github.com/hugolafaye/BeadTracking">https://github.com/hugolafaye/BeadTracking</a>. The files contain the variable 'trackData' being a cell array of tracking matrices. There is one tracking matrix for each image of the sequence giving in particular the coordinate and velocity of each bead. Complete information on data format is given in the file readme.txt in the github BeadTracking package. Parameter files necessary to replicate our results from the images are also available on the BeadTracking package as well as on <a href="https://doi.org/10.5281/zenodo.3454628">https://doi.org/10.5281/zenodo.3454628</a> where a 1000-image ground truth is stored.</p> <p>Important note: Experimental images were grabbed with the flow from right to the left implying for instance negative values for the x-coordinate of velocities. To comply with a traditional convention, images and associated results in the publication are shown from left to the right.</p> <p> </p>
Seismic modeling of bedload transport in a gravel-bed alluvial channel
<p>This repository publishes data for 4 flow events at the Arroyo de Los Pinos on the paper "Seismic modeling of bedload transport in a sandy gravel-bed alluvial channel".</p>
Dataset: Wood retention at inclined bar screens: effect of wood characteristics on backwater rise and bedload transport
<p>This dataset includes flow and bedload transport measurements and wood accumulation characteristics of flume experiments conducted at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.</p>
Discrete and continuum simulations of bedload transport with kinetic theory of granular flow
<p>This depository contains the simulation results used in the publication Chassagne, R., Chauchat J. & Cyrille B. (2023). A frictional-collisional model for bedload transport based on kinetic theory of granular flows: discrete and continuum approaches.</p> <p>It contains DEM results as well as the results of the continuum model. The results are written in text files containing headers with name and units of the variables.</p>
Suspended sediment load and bedload flux from the Glacier d'Otemma proglacial forefield (summers 2020 and 2021)
<p>The Glacier d’Otemma proglacial margin, located in the Swiss Alps at an altitude of about 2450 m a.s.l. (45.93423 N, 7.41160 E), is characterized by a ca. 1 km long by 200 m wide active braided forefield. In this setting we installed two gauging stations for the monitoring of both suspended sediment and bedload transport within the proglacial margin: GS1 at about 350 m from the glacier terminus and GS2 at the forefield outlet.</p> <p>Monitoring stations were equipped with water pressure sensors (CS451 from Cambell Scientific), turbidity probes (OBS300+ from Cambell Scientific) and geophones (3-components PE-6/B from Sensor Nederland connected to a DiGOS DATA-CUBE type 2 logger). Water discharge were determined following modalities described in Müller and Miesen (2022). Suspended loads were quantified using a conventional turbidity-suspended sediment concentration relationship, while bedload transport was derived seismically using the geophysical Fluvial model inversion (FMI) algorithm developed in Dietze et al. (2018). The dataset covers summers 2020 and 2021.</p> <p> Further details on data aquisition and post-processing techniques are available in Mancini et al. (2023).</p>
Data for manuscript "Estimating grain stress and distinguishing between mobility and transportability improves bedload transport estimates in coarse-bedded mountain rivers"
<p>This repository contains data collected that was used in the manuscript:</p> <p><span>Estimating grain stress and distinguishing between mobility and transportability improves bedload transport estimates in coarse-bedded mountain rivers</span></p> <p> </p>
Direct and indirect effects of increased bedload on algal and detrital-based stream food webs at the Coweeta Hydrologic Laboratory from 1997 to 1999: Tile/ sediment addition experiment, Summer 1997; Chlorophyll, AFDM, inorganics (days 5-40)
Anthropogenic sedimentation poses a significant threat to stream ecosystems throughout the world. Increases in bedload (sediment transported and deposited on the stream bottom) can be especially detrimental for benthic communities. To examine how increased bedload directly and indirectly affects stream communities, we simultaneously manipulated sediment and top-down effects of macroconsumers (fishes and crayfish) in situ in two factorial experiments, one using tiles and one using leaf packs as sampling substrates. Bedload was increased by adding small amounts of sediment (2.5 x normal levels) to localized areas (0.25 m2) of an otherwise unimpacted stream. This increase in bedload had direct effects on basal resources in both the tile and leaf pack experiments. In the tile experiment algal composition was altered by sediment addition, while in the leaf pack experiment fungal biomass declined with sediment.
Arroyo de los Pinos Bedload and Seismic Data
<p>This dataset contains hydrologic and power-spectral density data during several flash flood events at the Arroyo de los Pinos. Velocity miniseed files (seismic data) for each event is also included.</p>
Data for Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel
<p>Seismic dataset used in submitted manuscript "Seismic Noise and Subsurface Velocity Characterization for a Unique Bedload Monitoring Observatory in a Dryland Ephemeral Channel".</p>
Experiments on a single large particle segregating in bedload transport
<p>This depository contains all the data presented in "Experiments on a single large particle segregating in bedload transport" from H. Rousseau, J. Chauchat and P. Frey in Physical Review Fluids, as well as the code to read these data.</p> <p>There are 10 folders that each correspond to a configuration (i.e. size ratio and Shields number). These folders contain subfolders that correspond to the different repetitions we made for each configuration. In a subfolder, one can find:<br>- The first image of the experiment (t=0s).<br>- An hdf5 file called "bedAndWaterLines.h5" which contains the data for the waterline positions and the bedline positions with time.<br>- An hdf5 file called "frame_0_to_3000_with_step_1_and_shift_1.hdf5" which contains the granular bed velocity fields Ux and Uy interpolated over the time. These velocities have been obtained using the OpyFlow toolbox (https://github.com/groussea/opyflow.git).<br>- An hdf5 file called "DataTracked.h5" which contains the results from the detection of the intruder. Inside "DataTracked.h5", one can find one folder by timestep that includes the coordinates of the intruder. The total number of frame, the acquisition rate and the scale are also saved as datasets in "DataTracked.h5".</p> <p>The code "plotData.py" has been coded in python3 and allows one to read the data from the hdf5 files (make sure you installed the h5py package for python before). "plotData.py" is annotated and thus, it contains all the instructions to plot the data of a given repetition. It is based on the following classes:<br>- "LoadResult" that reads "DataTracked.h5"<br>- "loadWaterAndBed" that reads "bedAndWaterLines.h5"<br>- "readOpyf" that reads "frame_0_to_3000_with_step_1_and_shift_1.hdf5"</p> <p> </p> <p>The file "listRepetitions.ods" is also provided. It allows one to match a given experiment in the paper to its name in this depository.</p> <p>Do not hesitate to contact us if you need more info.</p>
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