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70 results for “water resources”
CAT, TD, ADCP data for CAT research paper to be published in Journal of Water Resource Research
<p>This file contain experiment data obtained in Huangcai reservoir, Hunan, China in September, 2020. The field experiment aimed to reconstruct multi-layer current field using three-dimensional inversion technique to visualize spatiotemporal current structure.</p>
Data for the paper 'A Novel Simulation Optimization Framework for Multi Scale Irrigation Water Distribution and Scheduling Considering Crop Growth Process' submitted to Water Resources Research, an AGU journal
<p>This data set contains the data for the paper 'A Novel Simulation Optimization Framework for Multi Scale Irrigation Water Distribution and Scheduling Considering Crop Growth Process' submitted to Water Resources Research, an AGU journal. <span>The settings and crop parameters are consist of maize</span><span><span>(</span></span><span><a title="Ran, 2018 #74" href="#_ENREF_44"><span>Ran et al., 2018</span></a></span><span>; </span><span><a title="Shirazi, 2021 #75" href="#_ENREF_48"><span>Shirazi et al., 2021</span></a></span><span>)</span><span></span><span>, flower</span><span><span>(</span></span><span><a title="Reyhaneh alsadat Mousavi Zadeh Mojarad, 2018 #83" href="#_ENREF_45"><span>Reyhaneh alsadat Mousavi Zadeh Mojarad, 2018</span></a></span><span>; </span><span><a title="Karimi Avargani, 2023 #80" href="#_ENREF_24"><span>Karimi Avargani et al., 2023</span></a></span><span>)</span><span></span><span> and wheat</span><span><span>(</span></span><span><a title="Iqbal, 2014 #76" href="#_ENREF_17"><span>Iqbal et al., 2014</span></a></span><span>; </span><span><a title="Huang, 2022 #79" href="#_ENREF_15"><span>Huang et al., 2022</span></a></span><span>; </span><span><a title="Lyu, 2022 #99" href="#_ENREF_38"><span>Lyu et al., 2022</span></a></span><span>; </span><span><a title="Karimi Avargani, 2023 #80" href="#_ENREF_24"><span>Karimi Avargani et al., 2023</span></a></span><span>)</span><span></span><span>,</span><span> which used for initializing AquaCrop-OS . </span></p>
Data for Cooper et al., 2023, 4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks, Advances in Water Resources
<p>Tomography dataset associated with Cooper, et al. (2023), "4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks" in Advances in Water Resources.</p>
Data from: Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States
Open the record for dataset details and reuse information.
Data for "Applying Heat and Humidity using Stove Boiled Water for Decontamination of N95 Respirators in Low Resource Settings"
<p>Raw Data</p>
Visualization of the Multidimensional Volumetric Data-base by Video - Mapping Technology in field of Operational Oceanography (Algerian basin) (zooplankton expressed as carbon in sea water - mass concentration of chllorophyl a in sea water,Wekeo Data ) During 2022 year : (educational support resource in space oceanography)
<p>The multidimensional view of the Earth and its immediate environment that is provided by space borne sensors, operating at many wavelengths and directed at many different phenomena, has revolutionized man's understanding of his planet and the surrounding space environment.<strong>(John H. McElroy.,1985)</strong>,</p> <p>Earth observation satellites measuring in the visible and infrared spectral domain provide a global perspective for many required to determine the role of the ocean in the global climate system, as well as the effects on the ocean of a changing climate <strong>(James A. Yoder and all.,2014)</strong>.</p> <p>Data visualization by video graphics technology is a digital modeling technique also a description or analogy used to help visualize something that cannot be observed directly which exploits the bases of scientific knowledge in a data processing system by the use of mathematical and statistical tools and analysis and forecasting methods to visualize what is hidden behind the data. This work is inspired by the general principle of numerical modeling and data processing, which takes into consideration (the observation of natural phenomena, and the statistical processing of scientific data, which are at the base of the functioning of natural variation)</p> <p> </p> <p><strong>Bibliographic reference:</strong><br> <strong>-Monitoring Earth's Ocean, Land, and Atmosphere from Space-Sensors, Systems, and Applications, edited by Abraham Schnapf, American Institute of Aeronautics and Astronautics, 1985<br> -Optical Radiometry for Ocean Climate Measurements, Elsevier Science & Technology, 2014</strong></p> <p> </p>
A Method of Water Resources Accounting Based on Deep Clustering and Attention Mechanism under the Background of Integration of Public Health Data and Environmental Economy
<p>A dataset and code for paper</p>
Carbon restoration potential on global land under water resource constraints
<p>The files contain the dataset and matlab code for the paper "Carbon restoration potential on global land under water resource constraints". </p> <p>Peng Shouzhang, Terrer César, Smith Benjamin, Ciais Philippe, Han Qinggong, Nan Jialan, Fisher Joshua B., Chen Liang, Deng Lei, Yu Kailiang. Carbon restoration potential on global land under water resource constraints. Nature Water, 2024, 2, 1071-1081. https://doi.org/10.1038/s44221-024-00323-5.</p>
Dataset for Water Resource / Forest Restoration Modeling in Tahoe-Central Sierra Region
<p>This dataset includes materials related to a water resource modeling project in the Tahoe-Central Sierra Initiative (TCSI) region. The project used the DHSVM and LANDIS-II models to predict the potential hydrological impacts of various forest management scenarios related to partial or full restoration of the historic forest disturbance return interval.</p> <p>This dataset includes:</p> <ol> <li>Folders for each figure in the submitted manuscript, including data and scripts needed to reproduce the figures.</li> <li>Model results, including CSV files of raw streamflow outputs from DHSVM, a combined CSV file of mass/energy balance outputs from DHSVM, and geoTIFF rasters of various snowpack states from DHSVM. Additionally, post-processed data are included, such as aggregated streamflow products and comparisons between management scenarios.</li> <li>Ancillary data related to the model setup, calibration, and scenario implementation, including meteorology, configuration files, watershed boundaries, output vegetation maps from LANDIS-II used as inputs to DHSVM, and calibration reference data.</li> </ol>
Data and generating files for the manuscript "A Multi-Model Analysis of Solute Plume Behavior in a Synthetic Braided-River Deposit", submitted to Water Resources Research, August 2018.
<p>Data and generating files for the manuscript "A Multi-Model Analysis of Solute Plume Behavior in a Synthetic Braided-River Deposit", submitted to Water Resources Research, August 2018.</p> <p>This zipped folder contains the codes and data generated for the manuscript. The main routine for generating the ensembles is fidelity/run_fidelity.py. The folders 'dtgeostats', 'flowtrans', and 'hyvr' contain utilities for generating parameter fields and running flow-and-transport simulations. Note that the codes and data are provided as-is and relative pathways, etc. in the code may not function correctly. The data can be found in the fidelity/runfiles/braid005 directory and includes the outputs for the synthetic virtual reality (fidelity/runfiles/braid005/braid_vr) and the following model ensembles: object-based with no conditioning (fidelity/runfiles/braid005/braid_1a), object-based with soft conditioning (fidelity/runfiles/braid005/braid_1b), MPS (fidelity/runfiles/braid005/braid_2a/), isotropic multi-Gaussian (fidelity/runfiles/braid005/braid_3/isn/), and anisotropic multi-Gaussian (fidelity/runfiles/braid005/braid_3/ann/) .</p>
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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.