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396 results for “Surface water”
Modulating the Surface Properties of Lithium Niobate Nanoparticles by Multifunctional Coatings Using Water-in-Oil Microemulsions
<p>Raw data associated to the study entitled <em>Modulating the Surface Properties of Lithium Niobate Nanoparticles by Multifunctional Coatings Using Water-in-Oil Microemulsions.</em></p> <p>Metadata file</p> <p>DLS measurements</p> <p>FTIR characterization</p> <p>Labbook</p> <p>NMR characterization</p> <p>TEM and EDX analysis</p> <p>XRD measurements</p>
Datasets of groundwater level and surface water budget in a central Mediterranean site (June 21, 2017 - October 1, 2022)
<p>The datasets contain data of groundwater levels and surface water budget measured in the Salento University Campus ‘Ecotekne’, in Lecce province, Italy (40°20’ N, 18°06’ E) between June 2017 and October 2022. The groundwater data are obtained from two historic wells (FW and BW) hand dug in the Miocene karst Aquifer of Central-Eastern Salento. They are close (few hundreds of meters) to the micrometeorological station of the CNR-ISAC (National Research Council Institute for Atmospheric Science and Climate), that provided the surface water budget data. </p> <p> </p>
Safe and Just Earth Systems Boundaries for Surface Water: Hydrologic Alteration of Environmental Flows
<p>Title: <strong>Safe and Just Earth Systems Boundaries for Surface Water: Hydrologic Alteration of Environmental Flows</strong> Author: Pamela A. Green (<a href="mailto:pg@pamelaagreen.com">pg@pamelaagreen.com</a>), Advanced Science Research Center, CUNY, New York, NY USA <a href="https://orcid.org/0009-0006-7803-8182">https://orcid.org/0009-0006-7803-8182</a></p> <p>The python Jupyter Notebook <strong>SafeJustEarthSysBnd_EstressCUNY-Griffith2022-23.ipynb</strong> and accompanying data sets represent spatial modelling for development of the safe and just surface water target for Working Group 3 of the Earth Commission for the Earth Commission Long Report and the "Safe and Just Earth Systems Boundaries" publication. The surface water target includes spatial modelling of the extent of global-scale hydrological alteration of environmental flows.</p> <p>All input datasets required to run the model are located under the <strong>ModelInput</strong> folder with raster data in zipped format to minimize space requirements. The code extracts the zipped files and then deletes the uncompressed files upon completion. All model outputs are located under the <strong>ModelOutput</strong> folder.</p> <p>Please reference the <strong>README.xlsx</strong> file for a full listing of the model input and output data files.</p>
High-resolution (5 m) surface water persistence map for 2021 in East-Africa
<p>Raster surface water image highlighting the percentage of time in 2021 that there was water at a certain pixel in East Africa. </p> <p>Script which classifies individual countries: <a href="https://code.earthengine.google.com/3f508773522979dfa62a75bda7750b5f?noload=true">https://code.earthengine.google.com/3f508773522979dfa62a75bda7750b5f?noload=true</a></p> <p>Script which combines the individual maps and filters the end-result: <a href="https://code.earthengine.google.com/ed8ee1bbade0b51f3759565b30da37ab?noload=true">https://code.earthengine.google.com/ed8ee1bbade0b51f3759565b30da37ab?noload=true</a></p> <p> </p>
High-Resolution Water Surface Slopes from Multi-Mission Satellite Altimetry
<p><strong>1. Summary</strong>:</p> <p>This dataset contains water surface slopes (WSS) every kilometer along 11 Polish rivers derived from cross-calibrated multi-mission satellite altimetry (<em>Schwatke et al. 2023a</em> (in review). ). The approach to derive WSS is based on a weighted least-squares approach, which is described in detail in <em>Schwatke et al. 2023b</em> (in review).</p> <p><strong>2. Data Formats</strong>:</p> <p>This dataset is provided in netCDF and shapefile formats. Each netCDF file contains the data of a single river and parameters such as river chainage, WSS, WSS error, location, and nearest centerline information from the SWORD database (v1.1, <em>Altenau et al., 2021</em>). The shapefile consists of five files (.cpg, .dbf, .prj, .shp, .shx) containing the data of the 11 Polish rivers. The attributes are identical to the netCDF, but the river name has been added.</p> <p><strong>3. Attribute Description</strong>:</p> <p>The attributes of netCDFs and shapefiles are described in the following list:</p> <ul> <li> <p><strong>river_chainage</strong>: The <em>river chainage</em> describes the distance from the river mouth to the location of each bin along the river (units: km)</p> </li> <li> <p><strong>wss</strong>: Water surface slopes (WSS) at each bin along the river. WSS are set to NaN/NULL for unprocessed lakes/reservoirs or short river segments (units: mm/km).</p> </li> <li> <p><strong>wss_error</strong>: Errors of WSS at each bin along the river. WSS errors are set to NaN/NULL for unprocessed lakes/reservoirs or short river segments (units: mm/km).</p> </li> <li> <p><strong>longitude</strong>: Longitude of the 1 km bins along the river (units: degree).</p> </li> <li> <p><strong>latitude</strong>: Latitude of the 1 km bins along the river (units: degree).</p> </li> <li> <p><strong>centerline_id</strong>: Nearest <em>centerline id </em>extracted from the SWORD database (v1.1, <em>Altenau et al., 2021</em>).</p> </li> <li> <p><strong>node_id</strong>: <em>Node id</em> from the SWORD database (v1.1, <em>Altenau et al., 2021</em>) for the corresponding <em>centerline id</em>.</p> </li> <li> <p><strong>reach_id</strong>: <em>Reach id</em> from the SWORD database (v1.1,<em> Altenau et al., 2021</em>) for the corresponding <em>centerline id</em>.</p> </li> <li> <p><strong>river_name</strong>: The name of the river is only available in the Shapefile.</p> </li> </ul> <p><strong>4. References</strong>:</p> <p><em>Schwatke C., Dettmering D., Passaro M., Hart-Davis M., Scherer D., Müller F. L., Bosch W., Seitz F.: </em><strong>OpenADB: DGFI-TUM`s Open Altimeter Database</strong>. Geoscience Data Journal, 2023a (in Review)</p> <p><em>Schwatke C., Halicki M., Scherer D</em>.: <strong>Generation of high-resolution water surface slopes from multi-mission satellite altimetry</strong>. Water Resources Research, 2023b (in Review)</p> <p><em>Altenau E.H., Pavelsky T.M., Durand M.T., Yang X., Frasson R.P.d.M., Bendezu L.</em>: <strong>SWOT River Database (SWORD) (Version v1)</strong> [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.4917236">https://doi.org/10.5281/zenodo.4917236</a>, 2021</p>
Temporal trends of surface water area in India's rivers and basins
<p>This dataset quantifies the extent and annual rate of change in surface water area (SWA) in India's rivers and basins over a period of 30 years from 1991 to 2020. Visit <a title="Surface Water Trends - India" href="https://sites.google.com/view/surface-water-trends-india/" target="_blank" rel="noopener">Surface Water Trends - India</a> for an interactive web interface to explore these results, and for additional data and information.</p> <p>It is derived from the <a href="https://global-surface-water.appspot.com/" target="_blank" rel="noopener">Global Surface Water Explorer</a> which maps terrestrial surface water globally using historical Landsat satellite imagery. (Pekel, J. et al., Nature 540, 418-422 (2016). (doi:10.1038/nature20584)). The data files contain zipped archives of shapefiles and CSV (comma separated values) files.</p> <p>Shapefiles are one for each season (dry, wet and permanent) and scale (river basin and reach) of our analysis, and contain annual trends in surface water area. To open and explore them in a GIS software (eg. QGIS), un-ZIP them and include them as vector datasets.</p> <p>CSV files are one for each scale (river basin and reach (transect)) of our analysis, and contain time series of surface water areas from 1991 to 2020. To open and explore them, for analysis or to explore in a table editing software, un-ZIP them and read them in.</p> <p>Refer to 00_README.txt for details on feature and table attributes in the files. </p>
Dataset of chemicals of emerging concern (CECs) in surface water in the Swedish west coast (Stenungsund)
<p>This repository encompasses the environmental concentrations of emerging chemical contaminants (CECs) present in surface water samples obtained from the west coast of Sweden, specifically Stenungsund.</p>
Dataset on concentrations of CECs / PMTs /vPvM chemicals in Northern Portugal - Galicia (NW Spain) surface waters and wastewaters
<p>Dataset of concentrations of different contaminants of emerging concern (CECs), including persistent mobile and toxic (PMT) and very persistent and very mobile (vPvM) chemicals, in raw and treated wastewater, inland and coastal water samples from Galicia (NW Spain) and the North of Portugal.</p> <p>Data is provided in MS Excel (xlsx) and CSV formats and contains chemicals data, concentrations, location of the samples (coordinates) and sampling date. Location of the wastewater samples is not provided ought to confidentiality agreement.</p> <p>Further details are provided in the associated publication:</p> <p><strong><a href="http://doi.org/10.1016/j.scitotenv.2023.163737"><em>R. Montes et al. Occurrence of persistent and mobile chemicals and other contaminants of emerging concern in Spanish and Portuguese wastewater treatment plants, transnational river basins and coastal water. Science of the Total Environment 2023, 885, 163737. DOI: </em>10.1016/j.scitotenv.2023.163737</a></strong></p> <p><strong>If you use this data, please cite this ZENODO deposit (DOI: <a href="https://doi.org/10.5281/zenodo.6603302">10.5281/zenodo.6603302</a>) and the associated publication mentioned above (DOI: <a href="http://doi.org/10.1016/j.scitotenv.2023.163737">10.1016/j.scitotenv.2023.163737</a>)</strong></p>
Global 10-m spatial distribution of Water-surface photovoltaics (2019-2021)
<p>The recent boom in solar photovoltaics has intensified global competition for land use. Water-surface photovoltaics (WSPV) has also increased globally as an efficient alternative to land-based photovoltaics. Determining the spatio-temporally distribution of WSPVs is essential for estimating renewable energy capacity, evaluating the associated socio-environmental impacts, and managing and planning WSPV projects. However, a comprehensive inventory of WSPV locations and extent on the global scale is still lacking. To address these issues, we developed a workflow for identifying WSPVs using time-series optical satellite images and generated the first global-scale WSPV inventory map, with overall accuracy exceeding 96%.</p>
Data from: Can IR images of the water surface be used to quantify the energy spectrum and the turbulent kinetic energy dissipation rate?
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Distance from available surface water of mammals in Ruaha National Park
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Dataset: Surface waters in socially vulnerable areas are disproportionately under-monitored for nutrients in the U.S. South Atlantic-Gulf Region
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Everglades Saltwater Intrusion Marsh Surface Water Dissolved CO2 June 19th to 25th 2022
Dissolved CO2 (ppm) was measured in surface water at the Everglades saltwater intrusion marsh eddy covariance flux tower (US-EvM on AmeriFlux) for one week in June 2022. Minute resolution measurements were made using the CO2-LAMP (Blackstock et al., 2019).
Semi-quantitative microcystin concentration measured in surface water samples collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2015-2018
Included in this data package are cyanobacterial toxin data from the Citizen-Led Environmental Observatory (CLEO), a volunteer water quality monitoring program run by Friends of the Lake (FOTL, friendsofthelake.org) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (toxin data available form 2015-2018). Trained volunteer monitors collect routine surface water samples from multiple nearshore sites twice a month from Memorial Day through Labor Day. In addition, spot samples are taken whenever a significant algae bloom is present at the collection site. These samples are analyzed for microcystin concentrations. Routine water samples are also analyzed for levels of the total nitrogen and phosphorus concentrations. Additionally, CLEO volunteers collect data on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum every 1-3 days during the same period. These data are available in EDI packages EDI567 (general water quality) and EDI568 (nutrients).
Napa River Watershed, U.S.A. soil leachate and surface water sulfate sulfur isotopes and concentrations
Sulfur (S) is widely used in agriculture, yet little is known about its fates and consequences within upland, mixed land-use land-cover watersheds. This dataset includes samples collected throughout the Napa River Watershed, California, U.S.A., where high S applications to vineyard agriculture are common. Sample collection focused on tracing the agricultural S “fingerprint” —or the combined S stable isotope composition and concentration of sulfate—through the Watershed. We collected samples during California wet seasons (December – April) over three years (2017-2020). Samples included vineyard agriculture and non-agricultural (primarily forest, grassland, and shrubland) soil water, culvert outflows, tributaries to the Napa River, and Napa River surface water. The data table includes water sample sulfate concentrations and sulfate-S stable isotope measurements as well as the stable isotope composition of S fungicide samples.
Surface and hyporheic water chemistry of the Tanana River
The geochemistry of hyporheic water at two islands on the Tanana River. The chemistry of wells was sampled twice a month and analyzed for major solutes and dissolved gases. Samples were analyzed for Ca, Mg, Na, K, NH4, Cl, NO3, SO4, DOC, TDN, CH4, CO2, N2O, pH and conductivity.
Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest 2013-2016
These data are simultaneous and continuous measurements of carbon, water and energy fluxes of the terrestrial landscape. These fluxes are major regulatory drivers of the boreal climate system and form key linkages and feedbacks between the land surface, the atmosphere and the oceans. At the APEX project site, within Bonanza Creek Experimental Forest, this monitoring is repeated across a chronosequence of permafrost degradation; the Black Spruce site is an area of stable permafrost with intact black spruce forest (APEX gamma site), the Thermokarst site is an active thermokarst zone with considerable tree mortality (APEX betaSW site), the Fen site is within a stable treeless fen with deep active layer depth (APEX apexcon,low, and ele sites). The main variables being monitored are the instananeous fluxes of CO2, water vapor and surface energy (shortwave, longwave and net radiation), secondary variables included photosynthetically active radiation (PAR), air and soil temperatures, rainfall, snow depth, soil moisture content, wind direction and speed, and average atmospheric concentrations of CO2 and H2O through the year. Our site naming scheme is as follows: 1) gamma = Black Spruce site = YF_2472, 2) betaSW = Thermokarst site= BC_5166, 3) (apexcon+apexele+apexlow) = Fen site = BC_FEN
Assembled file of one minute averages for high resolution surface meteorological (Met) and sea water intake (SWI) data from continuous underway measurements from CCE LTER process cruises in the CCE region, 2006 - 2019.
As the research vessel is underway for the duration of a CCE Process Cruise (since 2006, ongoing), 30 parameters are continuously measured regarding the oceanographic surface and atmospheric and navigational environment of the vessel, along the ship's trackline in the CCE region.
Hubbard Brook Experimental Forest: W3 Surface Water Sampling Sites – 2009-2010
This dataset presents field and analytical data collected during a surface water sampling survey on six dates between July 9, 2009 and October 1, 2010 in watershed 3 (W3) at the Hubbard Brook Experimental Forest, NH, USA. Samples were collected every 50 meters along an ephemeral to perennial stream network and at groundwater seeps wherever they were located. The dataset includes both a table of chemical analyses and a shapefile of sampling site locations. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
PIE LTER diel surface water chemistry of two high marsh ponds, Rowley, MA, during the summer of 2016.
We measured diel fluctuations in surface water chemistry of two high marsh ponds in July 2016. The ponds are shallow and experience day-night swings in oxygen concentrations, from super-saturation to anoxia. Our goal was to characterize changes in geochemical properties and dissolved organic carbon concentrations that accompany wide swings in oxygen concentrations. These data provide information about the responsiveness of microbial communities and how the dominance of redox-sensitive metabolisms changes over short time scales (e.g., hours) to feed back on pond water chemistry.
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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.