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83 results for “fluvial”
Figure 3 in The influence of flood pulses on the reproductive strategy of two species of passalid beetle in the fluvial archipelago of Anavilhanas, Amazon, Brazil
Figure 3. Analysis using Pearson's correlation coefficient to test for a relationship between the pluviometric index and the number of larvae of Passalus abortivus between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State.
Figure 2 in The influence of flood pulses on the reproductive strategy of two species of passalid beetle in the fluvial archipelago of Anavilhanas, Amazon, Brazil
Figure 2. Analysis using Pearson's correlation coefficient to test for a relationship between the water level of the Negro River and the number of larvae of Passalus abortivus between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State.
Compound coastal, fluvial, and pluvial flooding during historical hurricane events in the Sabine-Neches Estuary, Texas
<p>This dataset contains boundary forcing (offshore water level and river discharge), topobathy, and Manning's n roughness data used to simulate compound flooding due to historical hurricanes (Harvey, Ike, and Rita) in the Sabine-Neches Estuary in Texas. It also includes water level outputs used for the analysis presented in the manuscript entitled: <em>Compound coastal, fluvial, and pluvial flooding during historical hurricane events in the Sabine-Neches Estuary, Texas </em>(<a href="https://doi.org/10.1029/2022WR033144">https://doi.org/10.1029/2022WR033144</a>).</p>
Dataset accompanying the publication: Reservoir mud releasing may suboptimize fluvial sand supply to coastal sediment budget: Modeling the impact of Shihmen Reservoir case on Tamsui River estuary
<p>Delft3D model input and output files for scenario simulations (Scenario 1, Scenario 2, and Scenario 3)</p>
Data from: Aquatic community structure across an Andes-to-Amazon fluvial gradient
Open the record for dataset details and reuse information.
Topographic Relief Response to Fluvial Incision in the Central Tibetan Plateau: Evidence From Cosmogenic 10Be
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The genesis and development of vegetated fluvial landforms follow the biogeomorphological succession model in a channelised river
<p>Statistical database for the publication "The genesis and development of vegetated fluvial landforms follow the biogeomorphological succession model in a channelised river" in ESP&L.</p>
Elevation data to accompany "A curvature-based method for measuring valley width applied to glacial and fluvial landscapes"
<p>This repository contains elevation data, derivatives, and manual measurements used in the manuscript "A curvature-based method for measuring valley width applied to glacial and fluvial landscapes" submitted to the Journal of Geophysical Research.</p> <p>This data is derived from the 1/3 arc-second (~10 m) resolution seamless digital elevation models from the 3D Elevation Program (3DEP) in the coterminous United States [0]. The Canadian Rockies study site uses 90 m resolution data derived from the Shuttle Radar Topography Mission (SRTM) dataset [1].</p> <p>Each study site corresponds to a single directory (e.g. 'valley_width/olympics/').</p> <p>Derivatives are stored in GeoTIFF format (with no file extensions) with the following naming conventions (shown for the Olympic Mountains study area). Manual width measurements are stored as Pickle files (e.g. 'olympics_width_fluvial.p') in the measurements/ subdirectory in each case.</p> <p>- olympics_area (Catchment area)<br> - olympics_elevation (Elevation)<br> - olympics_filled (Hydrologically corrected elevation)<br> - olympics_flow_direction (Flow direction)<br> - olympics_mask_fluvial (Binary mask of fluvial catchments)<br> - olympics_mask_glacial (Binary mask of glacial catchments)<br> - olympics_unnormalized_width (Valley width estimated without using scale normalization)<br> - olympics_width (Valley width estimated using scale normalization)</p> <p>Python scripts to reproduce the major figures and analysis and their EPS output are also included.</p> <p>References</p> <p>[0] <a href="https://www.usgs.gov/core-science-systems/ngp/3dep/about-3dep-products-services">https://www.usgs.gov/core-science-systems/ngp/3dep/about-3dep-products-services</a></p> <p>[1] <a href="http://srtm.csi.cgiar.org/srtmdata/">http://srtm.csi.cgiar.org/srtmdata/</a></p>
Dataset for ``Valley formation on early Mars by subglacial and fluvial erosion´´
<p>These datasets contain:</p> <p>-Morphometrical data for 66 Martian valley networks, as described in the study ``Valley formation on early Mars by subglacial and <br> fluvial erosion´´.</p> <p>- Shape files and raw data text files with MOLA altimetry data extracted from high resolution valley streamlines, for the purpose of longitudinal profile analysis. </p> <p>- Longitudinal profile observations, including the presence and interpretation of undulating sections. </p> <p>You are free to use and modify this data. If you do so, please cite the study </p> <p>Grau Galofre et al., 2020, ``Valley formation on early Mars by subglacial and fluvial erosion´´</p>
Supporting Information for "How erosion influence fault segmentation and earthquakes in thrust belts: Low-temperature thermochronology and fluvial shear stress analyses on the southern Longmen Shan, eastern Tibet"
<p>Supporting Information for</p> <p>How erosion influence fault segmentation and earthquakes in thrust belts: Low-temperature thermochronology and fluvial shear stress analyses on the southern Longmen Shan, eastern Tibet</p> <p>Yijia Ye<sup>1</sup>, Xibin Tan<sup>1, </sup>*, Yiduo Liu<sup>2</sup>, Feng Shi<sup>1</sup>, Yuan-Hsi Lee<sup>3</sup>, Michael A. Murphy<sup>2</sup>, Xiwei Xu<sup>4</sup></p> <ol> <li>State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, 100029, China</li> <li>Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77204-5007, USA</li> <li>Department of Earth and Environmental Sciences, National Chung-Cheng University, Chia-Yi, 62102, Taiwan</li> <li>Institute of Crustal Dynamics, China Earthquake Administration, Beijing, 100085, China</li> </ol> <p><em>* </em>Corresponding author. E-mail address: <a href="mailto:tanxibin@sina.com">tanxibin@sina.com</a></p> <p> </p> <p><strong>Contents of this file </strong></p> <p>Figures S1 and Table S1</p>
Data and code for the publication "Assessing the Behavior of Microplastics in Fluvial Systems: Infiltration and Retention Dynamics in Streambed Sediments" - Part 2(2)
<p><strong>Background</strong></p><p>The dataset contains data on Microplastic transport experiments run in an experimental flume of the University of Bayreuth. It was analysed in the paper by J.P. Boos, F. Dichgans, J.H. Fleckenstein, B.S. Gilfedder and S. Frei, "Assessing the Behavior of Microplastics in Fluvial Systems: Infiltration and Retention Dynamics in Streambed Sediments", currently under review in Water Resources Research</p><p> </p><p><strong>Description of the dataset</strong></p><p>This dataset contains data used for individual particle detection, and is a companion of the main dataset (10.5281/zenodo.10083568). The files need to be downloaded and merged into the given folder structure. Put the folder "1Pix" along with the folder "10Pix" to the folder in "210812/Data-FIS/matlab/2_Experiment/exp/".</p><p> </p><p><strong>Disclaimer</strong></p><p>The data and code are provided as is without any warranty.</p><p> </p><p><strong>Funding</strong></p><p>Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -– Project Number 391977956 –- SFB 1357.</p>
Data and code for the publication "Assessing the Behavior of Microplastics in Fluvial Systems: Infiltration and Retention Dynamics in Streambed Sediments" - Part 1(2)
<p><strong>Background</strong></p><p>The dataset contains data on Microplastic transport experiments run in an experimental flume of the University of Bayreuth. It was analysed in the paper by J.P. Boos, F. Dichgans, J.H. Fleckenstein, B.S. Gilfedder and S. Frei, "Assessing the Behavior of Microplastics in Fluvial Systems: Infiltration and Retention Dynamics in Streambed Sediments", currently under review in Water Resources Research</p><p> </p><p><strong>Description of the dataset</strong></p><p>This dataset is the main dataset used for the analysis. There is a twin archive connected to this one, which contains the dataset which was used for the individual particle detection routines (10.5281/zenodo.10081788). The files have to be downloaded and merged into the folder structure.</p><p>The following data is included</p><ul><li>individual experimental data and results in the folders<ul><li><strong>210812</strong> (10 µm, coarse sand, low-flow)</li><li><strong>220727</strong> (1 µm, coarse sand, low flow)</li><li><strong>220803</strong> (3 µm, coarse sand, low-flow)</li><li><strong>220818</strong> (1 µm, fine sand, low-flow)</li><li><strong>220901</strong> (1 µm, coarse sand, high-flow)</li></ul></li><li><strong>Comparison</strong> (comparing individual results of the experiments)</li><li><strong>Scripts</strong> (contains the individual matlab scripts)</li><li><strong>labbook.xlsx</strong> (contains metadata on the experiments, which are read out in the matlab scripts)</li></ul><p> </p><p><strong>Description of the code</strong></p><p>The matlab scripts *.m contain the code to read and analyse all experimental data. The scripts are divided for the different input file types.</p><ul><li>Main scripts to analyze experimental data<ul><li><strong>Experiment_Main.m </strong>Main routine for individual experiments, reading and analysing Fluorometer, Levelogger, Flowmeter, Ultrasonics PIV</li><li><strong>Experiment_Main_Compare.m </strong>Comparison of individual experiment results</li></ul></li><li>FIS-dataset<ul><li><strong>FIS_Cal_Individual.m: </strong>Realizes individual calibrations of one experiment</li><li><strong>FIS_Cal_Result.m: </strong>Merges individual calibrations of one experiment</li><li><strong>Experiment_FIS.m: </strong>Load data of one experiment, detect interfaces. Followed by<ul><li><strong>Experiment_FIS_1pix</strong>: Individual particle detection (for 10 µm experiment, no binning)</li><li><strong>Experiment_FIS_10pix</strong>: Particle cloud analysis (all experiments, binning 10 Pix * 10 Pix)</li></ul></li><li><strong>Experiment_FIS_10pix_compare.m: </strong>Compare results of particle cloud analysis for all experiments.</li></ul></li><li>Fluo-data<ul><li><strong>Fluo_Cal.m </strong>Realizes calibration for Fluorometer devices</li></ul></li><li>PIV-dataset<ul><li><strong>PIV_individual.m </strong>Individual analysis of Particle Image Velocimetry (in total 9 different subdatasets, from 3 camera positions, and each 3 different illumination positions)</li><li><strong>PIV_merge.m </strong>Merge<strong> </strong>9 individual results of PIV for a result for one experiment</li></ul></li><li>Profiler-dataset<ul><li><strong>Profiler.m </strong>Analyses data from bedform profiling (merging individual measurements after the experiment)</li><li><strong>Profiler_Compare.m </strong>Compares bedform elevations and metrics between the 5 experiments (acquired after the experiment)</li><li><strong>Profiler_Time.m </strong>Analyses temporal change of bedform elevation during the experiment</li></ul></li></ul><p> </p><p><strong>Disclaimer</strong></p><p>The data and code are provided as is without any warranty.</p><p> </p><p><strong>Funding</strong></p><p>Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -– Project Number 391977956 –- SFB 1357.</p>
FIGURE 5 in When roads cross streams: fish assemblage responses to fluvial fragmentation in lowland Amazonian streams
FIGURE 5 | ANOVA results for assemblage structure in northeastern Amazonian streams among stream reach groups. A. Taxonomic structure; B. Functional structure. D: Downstream reaches from impoundments; I: Impounded reaches; U: Upstream reaches from impoundments.
FIGURE 4 in When roads cross streams: fish assemblage responses to fluvial fragmentation in lowland Amazonian streams
FIGURE 4 | Relative contribution of turnover and nestedness component to total beta diversity obtained after averaging pairwise dissimilarities (Sørensen index) between stream reaches at each stream. D: Downstream reaches from impoundments; I: Impounded reaches; U: Upstream reaches from impoundments.
Data for "Mars' hourglass landforms as local source-to-sink fluvial systems"
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Channel Migration Patterns in Experimental Deltas: Implication for Fluvial Morphodynamics
<p>Digitized centerlines locations at every minute (300)</p>
Textural and compositional dataset of fluvial and aeolian sand in the Yarlung Tsangpo dune system
<p>The dataset comprises 5 tables including sample information, grain size distributions, grain roundness, sand petrography and heavy-mineral tables. The sample information table includes River/Dune types, names, locality, collected people, collected year and spatial coordinate, whereas other tables provide detailed sand textural and compositional information. The detailed textural and compositional dataset allow us to evaluate the differences between fluvial and aeolian sand in the river-fed Yarlung Tsangpo system, and The "multiple window" approach provides opportunity to explore intersample and intrasample variability, and help to understand the grain-size control on sand texture and composition. The dataset is a supplement to the manuscript "Fluvial-aeolian interaction and compositional variability in the river-fed Yarlung Tsangpo dune system (southern Tibet)" by Liang et al. (2023) submitted to JGR: Earth Surface. The data should <strong>NOT</strong> be used commercially.</p>
Fluvial shear stress data in the Longmen Shan
<p>The fluvial shear stress data and their related erosion rate in the Longmen Shan.</p>
Fig. 1 in Population dynamics of the migratory fish Prochilodus lineatus in a neotropical river: the relationships with river discharge, flood pulse, El Niño and fluvial megafan behaviour
Fig. 1. Map of the Pilcomayo River basin.
Fig. 2 in Population dynamics of the migratory fish Prochilodus lineatus in a neotropical river: the relationships with river discharge, flood pulse, El Niño and fluvial megafan behaviour
Fig. 2. Fish trap in the Pilcomayo River. In the inset the Sábalo (Prochilodus lineatus).
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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.