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30 results for “supplemental water”
Supplemental data and code for "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff"
<p>This dataset provides all data compiled and generated for the manuscript entitled "Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff" (https://doi.org/10.1016/j.oneear.2023.08.002). This includes the boundaries for 3614 hydrological catchments, the curated data used for analysis and modelling, the developed machine learning model, shapley values and area of applicability results, and data for global extrapolation</p> <p>It also contains a markdown file ('code.html') which shows how to access and use the data, and generic sample codes used to generate these results.</p> <p> </p> <p> </p> <p> </p>
Tracing and visualisation of contributing water sources in a model of flood inundation: video supplement
<p>These are video supplement files to Wilson & Coulthard (2021), produced using version 1.8f-WS of CAESAR-Lisflood software, <a href="https://doi.org/10.5281/zenodo.5541122">available on Zenodo here</a>. For a full description of the methodology and case studies, please refer to the paper which is available here: <a href="https://doi.org/10.5194/gmd-2021-340">https://doi.org/10.5194/gmd-2021-340</a>.</p> <p>Video animations (no audio) for the following case studies are included:</p> <p>1. <strong>Carlisle, United Kingdom</strong> (carlisleanimation-sourcetracing.avi and carlisleanimation-depthonly.avi):</p> <ul> <li>Simulation of the January 2005 flood event at the confluence of the Rivers Caldew, Petteril and Eden, using a 5 m grid.</li> <li>Both water source tracing and depth only versions are provided.</li> <li>In the water tracing version, blue colours represent flows from the River Eden, reds are from the River Petteril and greens are from the River Caldew; darker shades represent deeper water. Available on YouTube here: <a href="https://youtu.be/xOtOi06cXvA">https://youtu.be/xOtOi06cXvA</a></li> <li>In the depth only version, darker shades of blue represent deeper water, with no information about the water source in a grid cell. Available on YouTube here: <a href="https://youtu.be/aFz-sPRGHVE">https://youtu.be/aFz-sPRGHVE</a></li> </ul> <p>2. <strong>Avon-Heathcote estuary in Christchurch, New Zealand</strong> (avonheathcoteanimation.avi):</p> <ul> <li>Simulation for July 2017, which included a high flow event on 22 July, using a model grid of 10 m.</li> <li>Blue colours represent flows from tide, reds are from the River Avon and greens are from the Heathcote River; darker shades represent deeper water.</li> <li>Available on YouTube here: <a href="https://youtu.be/Fczr5tczzXU">https://youtu.be/Fczr5tczzXU</a></li> </ul> <p>3. <strong>Amazon </strong>(amazonanimation.avi):</p> <ul> <li>Simulation at the confluence of the Solimões (mainstem Amazon) and Purus rivers in the central Amazon, Brazil, for the period of 1 October 2013 through December 2014, using a ~270 m model grid.</li> <li>Red colours are from the Solimões, green colours are from the Purus; darker shades represent deeper water.</li> <li>Available on YouTube here: <a href="https://youtu.be/PknAL_8fd1I">https://youtu.be/PknAL_8fd1I</a></li> </ul> <p>4. <strong>Planar slope</strong> (planaranimation.avi):</p> <ul> <li>A simple test case consisting of a 2000 x 1000 m planar slope (0.001 m/m), with walls added at 250 m intervals across the slope, each of which has several gaps through which water can flow. Model grid was 5 m.</li> <li>Eight water sources were traced in total, with three visualised in the animation: red = source 2, green = source 4, blue = source 6. Depths are shown in the middle plot.</li> <li>Available on YouTube here: <a href="https://youtu.be/DTw8ysJtx8o">https://youtu.be/DTw8ysJtx8o</a></li> </ul> <p>Please feel free to use these animations, under the terms of the CC-BY-4.0 license. Please provide a link back to this site and a citation to Wilson & Coulthard (2021).</p> <p>Reference:</p> <p>Wilson, M. D. and Coulthard, T. J.: Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation, Geosci. Model Dev. Discuss. [preprint], <a href="https://doi.org/10.5194/gmd-2021-340">https://doi.org/10.5194/gmd-2021-340</a>, in review, 2021</p>
June 2023 Supplement Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other)
<p><strong>June 2023 Supplement of Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other)</strong></p> <p><strong>Description</strong></p> <p>Supplementary dataset to:</p> <p>Buscombe, Daniel, Goldstein, Evan, Bernier, Julie, Bosse, Stephen, Colacicco, Rosa, Corak, Nick, Fitzpatrick, Sharon, del Jesús González Guillén, Anais, Ku, Venus, Paprocki, Julie, Platt, Lindsay, Steele, Bethel, Wright, Kyle, & Yasin, Brandon. (2022). Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB satellite images of coasts (water, whitewater, sediment, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7335647</p> <p>This supplemental dataset consists of 283 RGB images and 283 associated labels for semantic segmentation of Sentinel-2 and Landsat RGB satellite images of coasts. Of these, 77 images-label pairs also have a corresponding NIR and SWIR satellite image. The 4 classes are 0=water, 1=whitewater, 2=sediment, 3=other</p> <p>These images and labels have been made using the Doodleverse software package, Doodler*. These images and labels could be used within numerous Machine Learning frameworks for image segmentation, but have specifically been made for use with the Doodleverse software package, Segmentation Gym**.</p> <p>Imagery are a mixture of 10-m Sentinel-2 and 15-m pansharpened Landsat 7, 8, and 9 visible-band imagery of various sizes. NIR, SWIR, Red, Green, and Blue bands only</p> <p><strong>File descriptions</strong></p> <ol> <li>classes.txt, a file containing the class names</li> <li>images.zip, a zipped folder containing the 3-band images of varying sizes and extents</li> <li>labels.zip, a zipped folder containing the 1-band label images</li> <li>overlays.zip, a zipped folder containing a semi-transparent overlay of the color-coded label on the image (blue=0=water, red=1=whitewater, yellow=2=sediment, green=3=other)</li> <li>nir.zip</li> <li>swir.zip</li> </ol> <p><strong>References</strong></p> <p>Buscombe, Daniel, Goldstein, Evan, Bernier, Julie, Bosse, Stephen, Colacicco, Rosa, Corak, Nick, Fitzpatrick, Sharon, del Jesús González Guillén, Anais, Ku, Venus, Paprocki, Julie, Platt, Lindsay, Steele, Bethel, Wright, Kyle, & Yasin, Brandon. (2022). Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB satellite images of coasts (water, whitewater, sediment, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7335647</p> <p>*Doodler: Buscombe, D., Goldstein, E.B., Sherwood, C.R., Bodine, C., Brown, J.A., Favela, J., Fitzpatrick, S., Kranenburg, C.J., Over, J.R., Ritchie, A.C. and Warrick, J.A., 2021. Human‐in‐the‐Loop Segmentation of Earth Surface Imagery. Earth and Space Science, p.e2021EA002085<a href="https://doi.org/10.1029/2021EA002085">https://doi.org/10.1029/2021EA002085</a>. See <a href="https://github.com/Doodleverse/dash_doodler">https://github.com/Doodleverse/dash_doodler.</a></p> <p>**Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. <a href="https://doi.org/10.1029/2022EA002332">https://doi.org/10.1029/2022EA002332</a> See: <a href="https://github.com/Doodleverse/segmentation_gym">https://github.com/Doodleverse/segmentation_gym</a></p> <p> </p>
Data used in the Final Draft Scientific Basis Report Supplement in Support of Proposed Voluntary Agreements for the Sacramento River, Delta, and Tributaries Update to the San Francisco Bay/Sacramento-San Joaquin Delta Water Quality Control Plan
This dataset includes modeled data describing the potential benefits of the Voluntary Agreements (VAs) from the Final Draft Scientific Basis Report Supplement in Support of Proposed Voluntary Agreements for the Sacramento River, Delta, and Tributaries Update to the San Francisco Bay/Sacramento-San Joaquin Delta Water Quality Control Plan.
Supplemental data for "Widespread and rapid dynamics of subglacial water in the Canadian Arctic"
<h2>What's inside</h2> <p>This data set contains:</p> <ol> <li><strong>Inventory:</strong> The inventory of the active subglacial water bodies in the Canadian Arctic.</li> <li><strong>Workflows:</strong> Data analysis code that produces the study results. </li> <li><strong>Results:</strong> The derived ArcticDEM strip data and visualizations generated by this study.</li> </ol> <p>See "README.md" for more information.</p>
Supplemental Tables that will be submitted with Hydrothermal Seepage of Altered Crustal Formation Water Seaward of the Middle America Trench, Offshore Costa Rica
<p>This spreadsheet will be submitted to JGR Solid Earth with a manuscrpt titled "Hydrothermal Seepage of Altered Crustal Formation Water Seaward of the Middle America Trench, Offshore Costa Rica" by Parsons et al. Keywords include Ridge flank, hydrothermal, Middle American Trench, hydrogeology, formation water, and pore water. Three short highlights include:</p> <p>Pore water chemical profiles reveal sediment diagenesis and seepage speeds up to 1.7 cm yr<sup>-1</sup> resulting in a net flux of 0.1 L s<sup>-1</sup>.</p> <p>Crustal formation water is warm (~75ºC) and chemically altered, stemming from water-basalt reactions and diffusive exchange with pore water.</p> <p>This ridge-flank hydrothermal system is not hydrologically connected to the ventilated crust to the west or the trench to the east.</p>
Figure 2. Atractides elburzensis n in Checklist of the water mites (Acari, Hydrachnidia) of Iran: Second supplement and description of one new species
Figure 2. Atractides elburzensis n. sp., holotype male, Kheirud stream; A = idiosoma, dorsal view; B = idiosoma, ventral view; C = palp, medial view; D = I-L-5 and -6. Scale bars = 100µm.
Figure 4 in Checklist of the water mites (Acari, Hydrachnidia) of Iran: Second supplement and description of one new species
Figure 4. Number of water mites from China (Jinet al. 2010), India (Pešić et al. 2010b), Iran (present study), Turkey (Erman et al. 2010), Balkan Peninsula (Pešić et al. 2010a), Montenegro (Pešić et al. 2010a), Bulgaria (Pešić et al. 2010a), Greece (Pešić et al. 2010a), France (Smit & Gerecke 2010), The Netherlands (Smit et al. 2012), Germany (Gerecke & Lehmann 2005), Poland (Biesiadka 1997) and the Baltic countries (Estonia, Latvia and Lithuania - Smitet al. 2010).
Figure 3 in Checklist of the water mites (Acari, Hydrachnidia) of Iran: Second supplement and description of one new species
Figure 3. Sampling site ofAtractides elburzensisn. sp. (Mazandaran Province, Kheirud Kenar forest, stream Kheirud). Photo. V. Pešić
Shadow Spaces for Water Stress Adaptation: Supplemental Irrigation Application in Rainfed Fig Production
<p>Data Sources is a SPSS file. Common descriptive statistics and inferential statistics are used.</p>
Supplement to "Retrieval of an ice water path over the ocean from ISMAR and MARSS millimeter and submillimeter brightness temperatures"
<p>This data set is was used for the retrieval of ice water path of a precipitating frontal system west of the coast of Iceland using the millimeter/submillimeter radiometer International SubMillimetre Airborne Radiometer (ISMAR) and Microwave Airborne Radiometer Scanning System (MARSS) on board the (Facility for Airborne Atmospheric Measurements) FAAM BAE-146.</p> <p>It is a supplement to the journal article "Retrieval of an ice water path over the ocean from ISMAR and MARSS millimeter and submillimeter brightness temperatures", which will be published in Atmospheric Measurement Techniques (AMT).</p> <p>The data set consists of</p> <ul> <li>the observed brightness temperatures of ISMAR and MARSS (FAAM_Flight_B897_radiometer-data.zip)</li> <li>the simulated brightness temperatures of ISMAR and MARSS and the corresponding atmospheric states (FAAM_Flight_B897_simulation.zip)</li> <li>the retrieval training database, which has been used to train the neural network retrieval.</li> </ul>
Data supplementing the article "Benthic diatom communities in an Alpine river impacted by waste water treatment effluents as revealed using DNA metabarcoding" , submitted to Frontiers in Microbiology
<p>These data supplement the article"Benthic diatom communities in an Alpine river impacted by waste water treatment effluents as revealed using DNA metabarcoding" submitted to Frontiers in Microbiology: </p> <p>The directory contains the following files:</p> <p><strong>64 PGM sequencing files (raw data, fastq files) </strong>- one file is provided for each sample by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>Sample_Names.xlsx</strong> - contains the information relative to the 64 samples including: the ID used in Mothur analyses (corresponding to the name of the fastq files), the sample name and the raw reads number for each sample.</p>
Figure 1 in Checklist of the water mites (Acari, Hydrachnidia) of Iran: Second supplement and description of one new species
Figure 1. Map of Provinces of Iran.
Ice water path retrievals from Meteosat-9 with quantile regression neural networks: video supplement
<p>Supplementary videos used from in A. Amell, P. Eriksson, S. Pfreundschuh: Ice water path retrievals form Meteosat-9 with quantile regression neural networks.</p>
FIGURE 1 in Supplement to the Checklist of water mites (Acari: Hydrachnidia) from the Balkan peninsula
FIGURE 1. Trichothyas (Kashmirothyas) jadrankae sp. nov., female holotype: A = idiosoma, dorsal view; B = idiosoma, ventral view; C = palp, medial view; D = palp, lateral view; E = gnathosoma; F = genital field. Scale bars = 100 µm.
FIGURE 2 in Supplement to the Checklist of water mites (Acari: Hydrachnidia) from the Balkan peninsula
FIGURE 2. Trichothyas (Kashmirothyas) jadrankae sp. nov., female holotype: A = I-L-2-6; B = I-L-2-6; C = III-L; D = IV-L. Scale bar = 100 µm.
Supplemental from: Seasonal Variation in Thermal Biology and Water Balance in a Year-Round Active Neotropical Treefrog, Scinax fuscovarius
<p>This supplemental material is associated to the published article entitled: "Seasonal Variation in Thermal Biology and Water Balance in a Year-Round Active Neotropical Treefrog, Scinax fuscovarius" </p>
Supplemental Document 01 Figueiredo et al Water 2019
<p><strong>Supplemental Document: Publications used to generate Figure 1.</strong></p>
FIGURE 3 in Supplement to the Checklist of water mites (Acari: Hydrachnidia) from the Balkan peninsula
FIGURE 3. Number of water mite species recorded from different countries of the Balkan peninsula.
FIGURE 2 in Checklist of the water mites (Acari: Hydrachnidia) of Turkey: First supplement
FIGURE 2. Number of species per family added to the Turkish fauna since 2010.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.