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83 results for “fluvial”
Data and processing scripts from "Morphodynamic Preservation of Fluvial Channel Belts"
<p>This compilation contains data reported in the manuscript</p> <p>Cardenas, Lamb, Jobe, Mohrig, and Swartz, Morphodynamic preservation of fluvial channel belts.</p> <p>As of Nov 2022, this manuscript is submitted to SEPM (Society for Sedimentary Geology) journal <em>The Sedimentary Record.</em></p> <p>Compilation contains:</p> <p>(1) Table showing the edge coordinates of each channel belt in the associated manuscript.</p> <p>(2) Table showing centerline point coordinates.</p> <p>(3) Table showing all width measurements for each channel belt.</p> <p>(4) A compilation table showing representative geometric measurements for each belt.</p> <p>(5) A python script to generate paleoflow directions from centerline coordinates.</p> <p>(6) A script to generate various geometric measurements from belt edge coordinates.</p> <p>(7) A script to plot histograms of geometric measurements.</p>
Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
<p>Streams and rivers are important sources of nitrous oxide (N<sub>2</sub>O), a powerful greenhouse gas. Estimating global riverine N<sub>2</sub>O emissions is critical for the assessment of anthropogenic N<sub>2</sub>O emission inventories. The indirect N<sub>2</sub>O emission factor (EF<sub>5r</sub>) model, one of the bottom-up approaches, adopts a fixed EF<sub>5r</sub> value to estimate riverine N<sub>2</sub>O emissions based on IPCC methodology. However, the estimates have considerable uncertainty due to the large spatiotemporal variations in EF<sub>5r</sub> values. Factors regulating EF<sub>5r</sub> are poorly understood at the global scale. Here, we combine 4-year in situ observations across rivers of different land use types in China, with a global meta-analysis over six continents, to explore the spatiotemporal variations and controls on EF<sub>5r</sub> values. Our results show that the EF<sub>5r</sub> values in China and other regions with high N loads are lower than those for regions with lower N loads. Although the global mean EF<sub>5r</sub> value is comparable to the IPCC default value, the global EF<sub>5r</sub> values are highly skewed with large variations, indicating that adopting region-specific EF<sub>5r</sub> values rather than revising the fixed default value is more appropriate for the estimation of regional and global riverine N<sub>2</sub>O emissions. The ratio of dissolved organic carbon to nitrate (DOC/NO<sub>3</sub><sup>-</sup>) and NO<sub>3</sub><sup>-</sup> concentration are identified as the dominant predictors of region-specific EF<sub>5r</sub> values at both regional and global scales because stoichiometry and nutrients strictly regulate denitrification and N<sub>2</sub>O production efficiency in rivers. A multiple linear regression model using DOC/NO<sub>3</sub><sup>-</sup> and NO<sub>3</sub><sup>-</sup> is proposed to predict region-specific EF<sub>5r</sub> values. The good fit of the model associated with easily obtained water quality variables allows its widespread application. This study fills a key knowledge gap in predicting region-specific EF<sub>5r</sub> values at the global scale and provides a pathway to estimate global riverine N<sub>2</sub>O emissions more accurately based on IPCC methodology.</p> <p>This dataset is a global integrated N<sub>2</sub>O dataset including data from 4-year (2017-2020) in situ measurements of six large rivers in China, 3-year (2018-2020) in situ measurements of urban river networks in Beijing of China, and 825 measurements from 70 published papers over six continents. The data includes dissolved N<sub>2</sub>O concentration, biogeochemical (DOC, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, temperature, and DO), climatological (climate zones), and geographic (region, location, and land cover) information.</p>
Comparing thermal regime stages along a small Yakutian fluvial valley with point scale measurements, thermal modeling and near surface geophysics
<ul> <li>Dataset associated with the paper :</li> </ul> <p>"<em>Comparing thermal regime stages along a small Yakutian fluvial valley with point scale measurements, thermal modeling and near surface geophysics</em>"</p> <p>Emmanuel Léger 1 , Albane Saintenoy 1 ,Christophe Grenier 2,† , Antoine Séjourné1 , Eric<br> Pohl2,3 , Frédéric Bouchard4, Marc Pessel1 , Kirill Bazhin5 , Kencheeri Danilov5, François<br> Costard1 , Claude Mugler2 , Alexander Fedorov5 , and Ivan Khristoforov5 and Pavel<br> Konstantinov5<br> 1 Laboratoire Geosciences Paris-Saclay, Université Paris-Saclay, CNRS, GEOPS, 91405, Orsay, France.<br> 2 Laboratoire des Sciences du Climat et de L’Environnement (LSCE), CEA CNRS UVSQ, Université<br> Paris-Saclay, Gif-sur-Yvette, France<br> 3 Department of Geosciences, University of Fribourg, Fribourg, Switzerland<br> 4 Universite de Sherbrooke Département de géomatique appliquée, Sherbrooke, QC, CA<br> 5 Melnikov Permafrost Institute, Yakutsk, Yakutia.</p>
Geometrical forms and influencing factors of distributive fluvial system
<p>Distributive Fluvial System developed around Sugan Lake Basin is studied by using geographic information software such as Google Earth, Global Mapper and digital elevation model(DEM). The gradient, fan radius,draining basin area and perimeter,the area and perimeter of DFSs around Sugan Lake Basin are analyzed.</p>
Data from: Detrital shadows: estuarine food web connectivity depends on fluvial influence and consumer feeding mode
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Data from: The impact of river capture on fluvial terraces and bedrock incision
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Controls on Preservation of Fluvial Cross Strata in the Deposition-dominated Regime
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Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
Open the record for dataset details and reuse information.
Experimental fluvial-deltaic stratigraphic patches for machine learning applications
<p>Collection of 6,132 images (128 x 128 pixels) cropped from experimental stratigraphy produced in the Tulane Delta Basin, TDB-10-1, under temporally constant boundary conditions. The images are prepared to be used in a machine learning project.</p> <p>Each image is prefixed with a number [0-5] which indicates the strike section the image was selected from. The cropped strike sections are obtained from the archival dataset located on SEN: <a href="http://sedexp.net/catalog/tdb-10-1-tulane-delta-basin">http://sedexp.net/catalog/tdb-10-1-tulane-delta-basin</a>.</p> <p>After cropping from the strike sections, each image was processed with binarization and a sequence of morphological opening and closing operations. The code that did the processing can be obtained at <a href="https://github.com/amoodie/StratGAN/blob/master/process_images/nrand_process.py">https://github.com/amoodie/StratGAN/blob/master/process_images/nrand_process.py</a>.</p> <p>This data was produced as part of a larger project: <a href="https://github.com/amoodie/StratGAN">https://github.com/amoodie/StratGAN</a></p>
Topographic Relief Response to Fluvial Incision in the Central Tibetan Plateau: Evidence From Cosmogenic 10Be
<p>Fluvial incision, regarded as one of the fundamental geomorphic processes, drives the evolution of mountainous landscapes. The transitional landscape from low-relief to high-relief in the central Tibetan Plateau is rapidly evolving as it is influenced by river dynamics, climate change and tectonic uplift. Combining cosmogenic <sup>10</sup>Be depth profile dating and topographic analysis, this study provides new constraints on the formation and destruction of low-relief surfaces in the central Tibetan Plateau. We find that the high-relief landscape in the Suoqu area (a major tributary of the upper Nu River) shows a rapid fluvial incision rate of 710 ± 70 mm kyr<sup>−1</sup> since the late Pleistocene, while the low-relief topography in the adjacent Xiaqiuqu area presents an order of magnitude lower incision rate of 70 ± 10 mm kyr<sup>−1</sup>. These results are consistent with the long-term (multi-million-year) exhumation rates derived from low-temperature thermochronology, suggesting that this region has experienced an evolving incision history. We interpret that the higher relief was caused by enhanced fluvial incision, and the lower relief was slowly developed by sedimentation and relatively steady low exhumation rate. The presence of a knickzone appears to mark the boundary between these differentially incising landscapes, which may be caused by rapid headward retreat and higher river discharge in the Suoqu River. The coincidence of fluvial terraces ages with climate-driven events, in addition to paleodenudation rates, indicates that the formation of fluvial terraces in the Xiaqiuqu and Suoqu areas might be associated with the quick sedimentation of weathered materials in early warming periods.<span> </span></p>
Distribution. Amazonian lowlands of E Brazil S of the Amazon River, extending S to the cerrado biome in EC Brazil, primarily in the Rio Tapajos, Rio Xingu, and Rio Tocantins-Araguaia fluvial systems of Para, Maranhao, Tocantins, Minas Gerais, Goias, and Mato Grosso states. in Echimyidae
Distribution. Amazonian lowlands of E Brazil S of the Amazon River, extending S to the cerrado biome in EC Brazil, primarily in the Rio Tapajos, Rio Xingu, and Rio Tocantins-Araguaia fluvial systems of Para, Maranhao, Tocantins, Minas Gerais, Goias, and Mato Grosso states.
Limits to Timescale-Dependence in Erosion Rates: Quantifying Glacial and Fluvial Erosion across Timescales
<p>Archive of data and code for the associated manuscript "Limits to Timescale-Dependence in Erosion Rates: Quantifying Glacial and Fluvial Erosion across Timescales". The "data" folder our global compilation of glacial and nonglacial erosion rates and associated metadata, beryllium data, lithology data, average regional hillslope data, and relevant prior compilations from the literature. The "src" folder contains Julia code to recreate paper figures as well as Julia and MATLAB code of the numerical model. </p>
Supplements for Inferring Long-Term Tectonic Uplift Patterns from Bayesian Inversion of Fluvially-Incised Landscapes paper
<p><strong>Data and File Organization:</strong></p> <ol> <li><strong>Natural Landscapes (DEM):</strong> <ul> <li>Look for <code>.tif</code> files containing DEMs of natural landscapes. These files are in latitude-longitude coordinates; convert them to UTM if needed.</li> </ul> </li> <li><strong>Synthetic Landscapes (DEM):</strong> <ul> <li>DEM files for synthetic landscapes, ready for use in inversion schemes, are labeled with a <code>syn_</code> prefix.</li> </ul> </li> <li><strong>Climatic Data:</strong> <ul> <li>Climatic data for the Himalayas is available in <code>climate_data_him.zip</code>.</li> </ul> </li> </ol> <p><strong>Running the Code:</strong></p> <ol> <li> <p><strong>Loading DEMs:</strong></p> <ul> <li>Use the <code>loadDEM</code> package to load your DEM file.</li> <li>Specify <code>Z0</code> and <code>A0</code> values, then plot the landscape and <code>basinID</code> for reference.</li> </ul> </li> <li> <p><strong>Identifying Basins of Interest:</strong></p> <ul> <li>Determine which <code>basinID</code>s are of interest, then save them as forward objects. The functions for this process are available within the relevant packages.</li> </ul> </li> <li> <p><strong>Loading the Forward Model:</strong></p> <ul> <li>Load the forward model from the saved file using the appropriate function in the <code>frd</code> package.</li> <li>Choose the number of knots and specify if you prefer a 1D or 2D inversion.</li> </ul> </li> <li> <p><strong>Running and Plotting Inversion Results:</strong></p> <ul> <li>After running the inversion, view results in <code>inversion.step</code>.</li> <li>Plot these results using the plotting functions in the <code>frdplotting</code> package.</li> </ul> </li> </ol> <p> </p> <p> </p> <p><strong>Setup and Installation:</strong></p> <ul> <li>Install the package <code>scabbard</code> with: <div> <div> </div> <div><code>pip install pyscabbard </code></div> </div> </li> <li>All other Python dependencies are standard and can be installed via <code>pip</code> or <code>conda</code> as needed.</li> </ul>
Data from: Aquatic community structure across an Andes-to-Amazon fluvial gradient
Aim: Little is known about factors affecting the elevational and longitudinal zonation of tropical Andean stream communities. We investigated epilithon, macroinvertebrate and fish assemblages along a 4100-m elevational–longitudinal gradient in an Andean headwater of the Amazon Basin. We interpret our results within the context of environmental factors, emphasizing temperature, as well as ecological theory relating shifts in metazoan functional feeding groups to shifts in basal resources along the fluvial continuum. Location: Arazá-Inambari-Madre de Dios watershed, south-eastern Peru. Methods: We sampled water physicochemistry, epilithon and macroinvertebrate diversity and abundance, and fish diversity at 18 main-stem and 14 tributary sites from high puna grasslands (4300 m a.s.l.) to Amazon Basin lowlands (200 m a.s.l.). Results: Water physicochemical parameters and the taxonomic and ecological structure of invertebrate and fish assemblages displayed mostly nonlinear responses to elevation: water temperature and percentage of macroinvertebrate taxa identified as leaf shredders had U-shaped responses; dissolved oxygen and percentage of macroinvertebrate taxa identified as grazers had hump-shaped responses. Epilithon richness increased slightly with elevation whereas macroinvertebrate and fish richness decreased. Main conclusions: Elevational gradients in physicochemical parameters are insufficient to explain abrupt and nonlinear shifts in community taxonomic and functional structure. Rather, trophic interactions, including predation and longitudinal turnover in basal food resources, seem to exert a stronger influence on the distributions of Andean aquatic organisms. A steep elevational decline in relative taxonomic diversity of leaf-shredding (versus algae-grazing) insects supports the hypothesis that temperature affects the functional composition of insect assemblages via its influence on microbial decomposition rates. This relationship, and the distributions of several insect and fish species across narrow elevational bands, suggests that Andean stream communities may be sensitive to global warming. Placer mining and road building impacts have already altered stream community structure, including the absence of many benthic species from low-elevation habitats.
Figure 8 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 8. Monthly abundance of larvae of Passalus punctiger in the different developmental stages for the period between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State. Notes: Spotted line, first instar; black line, second instar; white line, third instar.
Figure 7 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 7. Analysis using Pearson's correlation coefficient to test for a relationship between the pluviometric index and the number of larvae of Passalus punctiger between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State.
Figure 6 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 6. 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 punctiger between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State.
Figure 5 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 5. Variation in the water level of the Negro River plotted against the monthly abundance of larvae of Passalus punctiger at the ecological station of Anavilhanas, Novo Airão, Amazonas State, between April 1996 and March 1997. Notes: Line, abundance of larvae; columns, average level (m).
Figure 4 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 4. Monthly abundance of larvae of Passalus abortivus in the different developmental stages collected between April 1996 and March 1997 at the ecological station of Anavilhanas, Novo Airão, Amazonas State. Notes: Spotted line, first instar; black line, second instar; white line, third instar.
Figure 1 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 1. Variation in the water level of the Negro River plotted against the monthly abundance of larvae of Passalus abortivus collected between April 1996 and March 1997 from 10 islands on the alluvial plain, which is periodically inundated, at the ecological station of Anavilhanas, Novo Airão, Amazonas State, Brazil. Notes: Line, abundance of larvae; columns, average level (m).
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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.