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47 results for “Sediment transport”
Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport
<p>This repository contains supporting data for *Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport,* submitted to Geophysical Research Letters.</p> <p>Delft3D Config for Q1000Qs100Hs15.docx → contains configuration file info for running the Delft3d simulation Q1000Qs100Hs15.</p> <p>Matlab 2022b was used to load Delft3D output files and process the data.</p> <p>WaveDelta_Depth&DepositThick.mat Contains:</p> <p>Depth → timesteps x 322 x 142. Timesteps are variable for each simulation.</p> <p>MSEDRiverSum → 4 x 322 x 142. Mass of sediments from riverine source at four intermediate timesteps. </p> <p>MSEDWaveSum → 4 x 322 x 142. Mass of sediments from longshore transport (LSTUp) source at four intermediate timesteps.</p> <p>VolRiverSum → 322 x 142. Final Volume of sediments from riverine source.</p> <p>VolWaveSum → 322 x 142. Final Volume of sediments from longshore transport (LSTUp) source.</p> <p>XCOR & YCOR are the X and Y grid coordinate locations for maps (322 x 142).</p> <p>Shift2&4km are used for cases highly skewed downdrift to correct for 0 location at the river mouth.</p> <p>Cerc_formula.mlx Computes CERC longshore transport for the simulation conditions.</p> <p>J.mlx calculates river mouth balance (J) values (Nienhuis et al. (2016)) presented in Figure S4. </p> <p>Additional 114 Figures are provided in Data_Visualization_Figures.rar to show Depth and thickness; subaqueous morphodynamics and depth and sediment transport (quiver).</p>
Simulations of proglacial forefield morphodynamics and sediment transport to changing boundary conditions
<p>This dataset includes the simulated sediment flux records, stream statistics (braiding index and bar proprieties), DEMs and inundation maps of a proglacial forefield under different boundary conditions. Further information are available in: </p> <p>Mancini, D., Nicholas, A.P., Roncoroni, M., Müller, T., Jenkin, M., Miesen, F., Dietze, M., Calvo, F. & Lane, S.N. (submitted). Simulations of proglacial forefield morphodynamics and their implications for the filtering of subglacial sediment export following glacier retreat. <em>Earth Surface Processes and Landforms</em>.</p> <p>General information:</p> <ul> <li>Domain size: 462 x 125 pixels</li> <li>Time step (sediment fluxes): 0.005 days</li> <li>Time tep (inundation maps, DEMs and stream stats): 0.2 days</li> </ul> <p>The model used to produce them is called eRiDynaS, and enquiries regarding its availability should be directed to a.p.nicholas@exeter.ac.uk.</p>
Data for Intra-seasonal variability in sediment provenance and transport processes in the Brahmaputra basin
<p>No description provided.</p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
<p><span>Riparian or aquatic vegetation thrives with seasons. The understanding of canopies' Submergence-Ratio SR (stems' height to water depth) influence on suspended sediments' transportation is still limited. Thus, Large Eddy Simulations (LES) coupled with the Discrete Phase Method (DPM) are used to investigate the particles' 3-dimensional distribution in a partially vegetated straight channel. The spanwise distribution of particles is quantified by the Probability Density Function (PDF), showing a non-uniformity of particles in time as quantified by the PDF variance. The findings and conclusions: (Ⅰ) With SR rising, the particles' depletion effects exerted by the vegetation-side mixing layer are improved along the interface between vegetated and vegetation-side bare channel region. However, the SR has little effect on the variance of the particles' PDF in the spanwise direction when the mixing layer is fully developed. (Ⅱ) During the developing stage of the over-canopy mixing layer, submerged vegetation with higher SR gain a stronger upwards (vertical) entrainment capability. </span><span>The case (SR=60%) has a higher sediment concentration than other cases in the fully developed vertical mixing layer region above canopy.</span><span> (III) </span><span>The vertical suspension of particles in the vegetation-side bare channel region is analysed. Particles migrating from the vegetated region are entrained into the vegetation-side bare channel region by turbulent structures. Nevertheless, the vertical concentration profile is more uniform in the vegetated region than in the vegetation-side bare channel at the same streamwise location. The cases SR=40% and 60% still have higher sediment concentrations than other cases in the vegetation-side bare channel's upper region.</span></p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
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Dataset supporting "Daily Timescale Analysis of Sediment Transport and Topographic Changes on a Mesotidal Sandy Beach under Low to Moderate Wave Conditions", by Rodríguez-Padilla et al., submitted to Marine Geology
<p>This dataset comprises seven Matlab structure files containing measurements from different instruments deployed at Barra del Estero Beach (Baja California, Mexico) during a one-week field experiment (10-16/June/2016).</p> <p>Dataset:</p> <ul> <li>Wind speed and direction (MET.mat)</li> <li>Offshore wave conditions (ADCP_22m.mat)</li> <li>Depth-averaged velocities and pressure data (ADCP_22m.mat; ADCP_4m.mat; ADCP_2m.mat) </li> <li>Burst-averaged velocities and suspended sediment concentration time series (NADV.mat; SADV.mat)</li> <li>Daily topographic maps</li> </ul> <p>Note: The time-vector in all files is expressed in local time (GMT-7). </p>
Dataset and mesh convergence study for the article: Implementing moving object capability in a two-phase Eulerian model for sediment transport applications
<p>This dataset includes the results for the article Implementing moving object capability in a two-phase Eulerian model for sediment transport applications (2024). OpenFOAM Journal.<br>The dataset consists of the results obtained to produce the figures of the manuscript and the mesh convergence test.</p>
Data related to "Near-bed sediment transport during offshore bar migration in large-scale experiments"
<p>Abstract: </p> <p>This paper presents novel insights into hydrodynamics and sediment fluxes in large-scale laboratory experiments with bi-chromatic wave groups on a relatively steep initial slope (1:15). An Acoustic Concentration and Velocity Profiler provided detailed information of velocity and sand concentration near the bed from shoaling up to the outer breaking zone including suspended sediment and sheet flow transport. The morphological evolution was characterized by offshore migration of the outer breaker bar. Decomposition of the total net transport revealed a balance of onshore-directed, short wave-related and offshore-directed, current-related net transport. The short wave-related transport mainly occurred as bedload over small vertical extents. It was linked to characteristic intrawave sheet flow layer expansions during short wave crests. The current-related transport rate featured lower maximum flux magnitudes but occurred over larger vertical extents. As a result, it was larger than the short wave-related transport rate in all but one cross-shore position, driving the bar's offshore migration. Net flux magnitudes of the infragravity component were comparatively low but played a non-negligible role for total net transport rate in certain cross-shore positions. Net infragravity flux profiles sometimes featured opposing directions over the vertical. The fluxes were linked to a standing infragravity wave pattern and to the correlation of the short wave envelope, controlling suspension, with the infragravity wave velocity.</p> <p>About the data:</p> <p>The data on beach profile (from mechanical profiler), velocity (from ACVP and ADV), sand concentration (from ACVP and OBS) and water surface elevation (from RWG, AWG and PT) measurements is given in .mat (MATLAB) files.</p> <p>The folder “Beach Profiles” contains the measurements from the mechanical profiler before and after each test. To save time, only the morphologically active section of the profiles was measured. Additionally, the folder contains the initial profiles at the start of a sequence (after application of the benchmark waves). Here the full profile was measured.</p> <p>The structure “MobFrame” contains the absolute cross-shore position of the mobile frame (from which detailed measurements were taken) in the considered tests.</p> <p>The folder “ACVP” contains structures with ensemble-averaged velocity and concentration measurements in vertical reference to the undisturbed bed level or a few bins below it (zeta0-coordinate system) sampled at 50.5051Hz. For better interpretation of the measurements, it also features the ensemble-averaged intrawave instantaneous erosion depth (bed elevation) and the upper limit of the sheet flow layer.</p> <p>The folder “ADV” contains structures with the ensemble-averaged ADV data of each test sampled at 100Hz. Apart from the velocity components of each ADV it contains the vertical elevation of each ADV with respect to the ACVP transceiver. The ADV measurements were not subject to the same vertical referencing procedure that was described in the paper for the near-bed ACVP measurements and a more or less constant distance to the bed was assumed.</p> <p>The folder “OBS” contains structures with the ensemble-averaged OBS data of each test sampled at 40Hz. Apart from the concentration measurements it contains the vertical elevation of the OBSs with respect to the ACVP transceiver.</p> <p>The folder “ETA” contains structures with the ensemble-averaged water surface elevation measurements in many different absolute cross-shore locations in the flume sampled at 40Hz.</p> <p>For visualizing the near-bed concentration data, which may not be as trivial as visualizing the rest of the data, an example of MATLAB code is given:</p> <p>%S=ACVP_xx; %to choose which ACVP file you want to look into<br> con=S.c;<br> con(con<1)=1; %to cater for the cells where the logarithm is not defined<br> xphase=linspace(0,1,length(S.solbed)).*ones(size(S.c,2),size(S.c,1));<br> figure; hold on; box on; <br> [C,h]=contourf(xphase,S.z,log10(transpose(con)),[0:0.1:3]); <br> cbh=colorbar; caxis([0 3]); <br> set(h,'edgecolor','none'); <br> tt=get(cbh,'Title'); set(tt,'String','$^{10}log(c)$ $[kg/m^3]$','Interpreter','Latex');<br> plot(xphase(1,:),S.solbed,'k','Linewidth',1.5);<br> plot(xphase(1,:),S.solflo,'r','Linewidth',1.5);<br> xlabel('$t/T_r$','Interpreter','Latex')<br> ylabel('$\zeta_0$ $[m]$','Interpreter','Latex')<br> set(gca,'Fontsize',18)</p> <p> </p> <p> </p>
Mechanism underlying the millennial scale variation of offshore sediment transport in the North Yellow Sea
<p>Sediment cores YC10 (length: 548 cm, water depth: 54 m) and YC26 (length: 435 cm, water depth: 15 m) were collected by hammer drilling on a fishing vessel from the NYS in July 2016. The sediment cores were split lengthwise, described, photographed, and subsampled in the lab. They were sliced into thin sections for trace element analyses at intervals of 4–10 cm according to the age model. The samples were freeze-dried under vacuum, and the fine fraction (< 63 μm) was sieved from the bulk samples for further geochemical analysis. The number of samples for REEs in cores YC10 and YC26 was 71 and 80, respectively, while those for Sr-Nd isotopes were 12 and 14, respectively.</p>
Data related to "Near-bed sediment transport processes during onshore bar migration in large-scale experiments. Comparison with offshore bar migration."
<p>Abstract:</p> <p>This paper presents novel insights into nearshore sediment transport processes during bar migration on the basis of large-scale laboratory experiments with bichromatic wave groups on a relatively steep initial beach slope (1:15). Insights are based on detailed measurements of velocity and sand concentration near the bed from shoaling up to the outer breaking zone including suspended sediment and sheet flow transport. The analysis focuses on onshore migration under an accretive wave condition but comparison to an erosive condition highlights important differences. Decomposition shows that total net transport mainly results from a balance of short wave-related, bedload net onshore transport and current-related, suspended net offshore transport. When comparing the accretive to the more energetic erosive condition, the balance shifts towards net onshore transport, and onshore migration, because the short wave-related transport does not decrease as much as the current-related transport. This is related to the effects of skewness and asymmetry combined with larger sediment entrainment and undertow magnitude under the erosive condition. Net transports from streaming in the wave boundary layer and from infragravity waves are noticeable but only play a subordinate role. Identified priorities for numerical model development include parametrization of wave nonlinearity effects and better description of wave breaking and its influences on sediment suspension. The present data, unique in their combination of high measurement detail with fully-evolving accretive beach profiles, help to improve numerical modeling of long-term morphological evolution.</p> <p>About the data:</p> <p>The folder “Beach Profiles” contains the measurements from the mechanical profiler before and after each test. To save time, only the morphologically active section of the profiles was measured. Additionally, the folder contains the initial profiles at the start of each sequence (after application of the benchmark waves). Here the full profile was measured.</p> <p>The structure “MobFrame” contains the absolute cross-shore position of the mobile frame (from which detailed measurements were taken) in the considered tests.</p> <p>The folder “ACVP” contains structures with ensemble-averaged velocity and concentration measurements in vertical reference to the undisturbed bed level or a few bins below it (zeta<sub>0</sub>-coordinate system as described in the paper). For better interpretation of the measurements, it also features the ensemble-averaged intrawave instantaneous bed elevation (erosion depth) and the upper limit of the sheet flow layer.</p> <p>The folder “ADV” contains structures with the ensemble-averaged ADV data of each test. Apart from the velocity components of each ADV they contain the vertical elevation of each ADV with respect to the ACVP transceiver. The ADV measurements were not subject to the same vertical referencing procedure that was described in the paper for the near-bed ACVP measurements.</p> <p>The folder “OBS” contains structures with the ensemble-averaged OBS data of each test. Apart from the concentration measurements in each OBS sensor they contain the vertical elevation of each OBS with respect to the ACVP transceiver.</p> <p>The folder “ETA” contains structures with the ensemble-averaged surface elevation data of each test (from different instruments as described in the paper). The location of each instrument is given in absolute cross-shore coordinates x.</p> <p> </p> <p>For visualizing the near-bed concentration data, which may not be as trivial as visualizing the rest of the data, an example of MATLAB code is given:</p> <p>%S=ACVP_xx; %to choose which ACVP file you want to look into</p> <p>con=S.c;</p> <p>con(con<1)=1; %to cater for the cells where the logarithm is not defined</p> <p>xphase=linspace(0,1,length(S.solbed)).*ones(size(S.c,2),size(S.c,1));</p> <p>figure; hold on; box on;</p> <p>[C,h]=contourf(xphase,S.z,log10(transpose(con)),[0:0.1:3]);</p> <p>cbh=colorbar; caxis([0 3]);</p> <p>set(h,'edgecolor','none');</p> <p>tt=get(cbh,'Title'); set(tt,'String','$log_{10}(c)$ $[kg/m^3]$','Interpreter','Latex');</p> <p>plot(xphase(1,:),S.solbed,'k','Linewidth',1.5);</p> <p>plot(xphase(1,:),S.solflo,'r','Linewidth',1.5);</p> <p>xlabel('$t/T_r$','Interpreter','Latex')</p> <p>ylabel('$\zeta_0$ $[m]$','Interpreter','Latex')</p> <p>set(gca,'Fontsize',18)</p>
Roles of Wind-Driven Currents and Surface Waves in Sediment Resuspension and Transport During a Tropical Storm
<p>Roles of Wind-Driven Currents and Surface Waves in Sediment Resuspension and Transport During a Tropical Storm</p>
Inefficient nitrogen transport to the lower mantle by sediment subduction
<p>Source data</p>
Data and software for "A numerical study of inhibiting effect and mechanism of thermal front on sediment transport in a stratified continental sea"
<p>Data and software for "A numerical study of inhibiting effect and mechanism of thermal front on sediment transport in a stratified continental sea"</p>
Dense vegetation hinders sediment transport towards saltmarsh interiors - Supporting data and source code (Part II: Main runs)
<p>This is Part II of the supporting data and source code for the paper entitled "Dense vegetation hinders sediment transport towards saltmarsh interiors", submitted to <em>Limnology and Oceanography Letters.</em> It contains all input and output files for every simulations used in the paper.</p> <p>Each zip file corresponds to a model run. </p> <p>TIGER_XX.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 0-100.<br>TIGER_XX_100.zip: Scenario XX, hydro-morphodynamics and vegetation dynamics, years 100-200.<br>TIGER_XX_HYYY.zip: Scenario XX, hydro-morphodynamics only, year YYY.</p> <p>Main scenarios:<br>- 01: Spartina (Figures 1-5, S3-S10)<br>- 02: Salicornia (Figures 1-5, S3-S10)<br>- 83: No vegetation (Figures 1-5, S3, S8-S10)</p> <p>Additional scenarios:<br>- 146: Spartina, low bulk drag coefficient (Figure S3)<br>- 147: Spartina, very low bulk drag coefficient (Figure S3)<br>- 148: Salicornia, low bulk drag coefficient (Figure S3)<br>- 149: Salicornia, very low bulk drag coefficient (Figure S3)<br>- 122: Spartina, low settling velocity (Figure S8)<br>- 123: Spartina, high settling velocity (Figure S8)<br>- 124: Salicornia, low settling velocity (Figure S8)<br>- 125: Salicornia, high settling velocity (Figure S8)<br>- 126: No vegetation, low settling velocity (Figure S8)<br>- 127: No vegetation, high settling velocity (Figure S8)<br>- 128: Spartina, low critical bed erosion shear stress (Figure S8)<br>- 129: Spartina, high critical bed erosion shear stress (Figure S8)<br>- 130: Salicornia, low critical bed erosion shear stress (Figure S8)<br>- 131: Salicornia, high critical bed erosion shear stress (Figure S8)<br>- 132: No vegetation, low critical bed erosion shear stress (Figure S8)<br>- 133: No vegetation, high critical bed erosion shear stress (Figure S8)<br>- 134: Spartina, low Partheniades constant (Figure S8)<br>- 143: Spartina, high Partheniades constant (Figure S8)<br>- 136: Salicornia, low Partheniades constant (Figure S8)<br>- 144: Salicornia, high Partheniades constant (Figure S8)<br>- 138: No vegetation, low Partheniades constant (Figure S8)<br>- 145: No vegetation, high Partheniades constant (Figure S8)<br>- 150: Spartina, low sediment dry bulk density (Figure S8)<br>- 151: Spartina, high sediment dry bulk density (Figure S8)<br>- 152: Salicornia, low sediment dry bulk density (Figure S8)<br>- 153: Salicornia, high sediment dry bulk density (Figure S8)<br>- 154: No vegetation, low sediment dry bulk density (Figure S8)<br>- 155: No vegetation, high sediment dry bulk density (Figure S8)<br>- 76: Spartina, replicate #1 (Figures S9-S10)<br>- 77: Spartina, replicate #2 (Figures S9-S10)<br>- 78: Spartina, replicate #3 (Figures S9-S10)<br>- 88: Spartina, replicate #4 (Figures S9-S10)<br>- 80: Salicornia, replicate #1 (Figures S9-S10)<br>- 81: Salicornia, replicate #2 (Figures S9-S10)<br>- 82: Salicornia, replicate #3 (Figures S9-S10)<br>- 89: Salicornia, replicate #4 (Figures S9-S10)<br>- 85: No vegetation, replicate #1 (Figures S9-S10)<br>- 86: No vegetation, replicate #2 (Figures S9-S10)<br>- 87: No vegetation, replicate #3 (Figures S9-S10)<br>- 90: No vegetation, replicate #4 (Figures S9-S10)</p>
Numerical data of hydrodynamics and sediment transport for three reference scenarios: N1, P, and N2
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Data for paper "Axial wind effects on stratification and longitudinal sediment transport in a convergent estuary during wet season"
<p>This is the COAWST model data used in the paper. </p>
Data for submitted paper "Lateral circulation and associated sediment transport in a partially-to-highly stratified estuary "
<p>Uploaded data include the png-format figures and the original data for all figures.</p>
WASHTREET - Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model
<p><strong>WASHTREET</strong><strong> -</strong> <strong>Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model.</strong></p> <p>This dataset contains the results from the tests carried out at a laboratory physical model in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain) as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>. The objective of the project is to perform a series of high-resolution experiments where urban surface wash-off and sediment transport through gully pots and pipes were accurately measured in laboratory-controlled conditions in a separate drainage system.</p> <p>The experimental facility is a 36 m2 full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. Further details of the physical model are provided in ‘1_Physical_model_description.pdf’. Two zip files with rain intensity distributions (‘2_Rain_intensity_maps.zip’) and model topographies (‘3_Elevation_data.zip’) complete physical model information as accurately measured inputs for hydraulic, wash-off and sediment transport experiments. ‘4_Hydraulic_tests_description.pdf’ describes experimental procedure, equipment, measuring points, results and data set files of the hydraulic characterization of the experiments. Data regarding these hydraulic tests is included in ‘5_Hydraulic_tests.zip’. In these tests, flow in both gully pots and in the pipe system outlet, and a total of 6 surface and 6 pipe depths were measured by ultrasound distance sensors for the different simulated rains.</p> <p>‘6_Washoff_tests_description.pdf’ includes information of the experimental initial conditions, the different sediment granulometries used, measuring points, experimental procedure and result files regarding wash-off and sediment transport experiments. Data files of a total of 23 tests are included in ‘7_Wash-off_tests.zip’. In these experiments, an initial mass of sediment is distributed over the model surface, and the wash-off and sediment transport processes are measured during a steady and uniform rainfall by total suspended solids (TSS) and particle size distribution (PSD) samples at the entrance of gully pots and at the pipe system outlet. Online turbidity measurements at pipe system outlet, pipe depths and flow at pipe system outlet are also measured during the experiments. Results regarding mass balances, which are performed at the end of the experiment to assess the final distribution of sediments, are also included. At last, some relevant photos and videos taken during the experiments are provided in ‘8_Multimedia.zip’. </p> <p>Flow measurements have been used in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">10.1016/j.jhydrol.2019.05.003</a>), together with the related datasets <a href="http://www.doi.org/10.5281/zenodo.3239401">WASHTREET - PIV data</a> and <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET - Structure from Motion data</a>, to calibrate a 2D shallow water model.</p> <p>The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU)</p> <p> </p> <p>Derived publications:</p> <ul> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. <em>Scientific Data</em>, <em>7</em>(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., Rieckermann, J., Cea, L., Puertas, J., & Anta, J. (2020). Global and local sensitivity analysis to improve the understanding of physically-based urban wash-off models from high-resolution laboratory experiments. <em>Science of The Total Environment</em>, <em>709</em>, 136152. <a href="https://doi.org/10.1016/j.scitotenv.2019.136152">https://doi.org/10.1016/j.scitotenv.2019.136152</a></li> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. <em>Journal of Hydrology</em>, <em>575</em>, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Development and Calibration of a New Dripper-Based Rainfall Simulator for Large-Scale Sediment Wash-Off Studies. <em>Water</em>, <em>12</em>(1), 152. <a href="https://doi.org/10.3390/w12010152">https://doi.org/10.3390/w12010152</a></li> </ul>
Improving predictions of critical shear stress in gravel bed rivers: identifying the onset of sediment transport and quantifying sediment structure: Dataset
<p>This dataset accompanies the paper: Hodge RA, Voepel HE, Yager EM, Leyland J, Johnson JPL, Sear DA, Ahmed S. Improving predictions of critical shear stress in gravel bed rivers: identifying the onset of sediment transport and quantifying sediment structure. In review for Earth Surface Processes and Landforms. </p> <p>These data are from Figure 3 to 6. The aim of this part of the paper was to assess different methods for measuring the grain-scale sediment structure of a gravel-bed river. The approaches used are direct measurements, terrestrial laser scanning, and CT scanning. </p> <p> </p>
Sediment transport data
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.