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396 results for “Surface water”
Рис. 3. Микроскульптура наружной (А, B) и внутренней (C, D) поверхностей глохидиальных створок Colletopterum piscinale, оЗ. ШакШинское. МасШтабные линейки 2 мкм. Fig. 3. Microsculpture of the outer (А, B) and inner (C, D) surfaces of glochidial valves of Colletopterum piscinale, Lake Shakshinskoye. Scale bars – 2 µm. in Morphology of glochidia of the anodontine bivalves of the genus Colletopterum (Unionidae) inhabiting water basins of Khakasia Republic and Chitinskaya Territory
Рис. 3. Микроскульптура наружной (А, B) и внутренней (C, D) поверхностей глохидиальных створок Colletopterum piscinale, оЗ. ШакШинское. МасШтабные линейки 2 мкм. Fig. 3. Microsculpture of the outer (А, B) and inner (C, D) surfaces of glochidial valves of Colletopterum piscinale, Lake Shakshinskoye. Scale bars – 2 µm.
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C). in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C).
Рис. 2. Laternula elliptica: А – раковина вЗрослого моллюска иЗ морЯ Дейвиса, L=87 мм, вид сбоку; Б – вид с дорсальной стороны (по: Егорова [1982]); В – расположение пустых раковин Laternula elliptica в осыпаюЩемсЯ песчаном грунте на склоне подводного холма (по рисунку иЗ полевого дневника Б.И. Сиренко, ЗИН РАН); Г – наружные отверстиЯ вводного и выводного сифонов Laternula elliptica (King, 1832) на поверхности грунта. Fig. 2. Laternula elliptica: А – shell of adult mollusc from the Davis Sea, L=87 mm, lateral view; Б – dorsal view (after: Егорова [1982]); В – empty shells of Laternula elliptica in friable sand on a slope of underwater hill (after sketch in the field journal of Dr. B.I. Sirenko, Zool. Inst. RAS); Г – external openings of inhalant and exhalant siphons of Laternula elliptica on surface of bottom deposits. in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 2. Laternula elliptica: А – раковина вЗрослого моллюска иЗ морЯ Дейвиса, L=87 мм, вид сбоку; Б – вид с дорсальной стороны (по: Егорова [1982]); В – расположение пустых раковин Laternula elliptica в осыпаюЩемсЯ песчаном грунте на склоне подводного холма (по рисунку иЗ полевого дневника Б.И. Сиренко, ЗИН РАН); Г – наружные отверстиЯ вводного и выводного сифонов Laternula elliptica (King, 1832) на поверхности грунта. Fig. 2. Laternula elliptica: А – shell of adult mollusc from the Davis Sea, L=87 mm, lateral view; Б – dorsal view (after: Егорова [1982]); В – empty shells of Laternula elliptica in friable sand on a slope of underwater hill (after sketch in the field journal of Dr. B.I. Sirenko, Zool. Inst. RAS); Г – external openings of inhalant and exhalant siphons of Laternula elliptica on surface of bottom deposits.
Data associated with "The Role of Magma Oceans in Maintaining Surface Water on Rocky Planets Orbiting M-Dwarfs"
<p>The data included here involves all simulations outlined in the manuscript "The Role of Magma Oceans in Maintaining Surface Water on Rocky Planets Orbiting M-Dwarfs", submitted to MNRAS. Files are divided between models with and without a basal magma ocean, as well as different host stars, different magma ocean saturation limits, and different fringe/sensitivity analysis checks. Files are further sub-divided based on our studied parameter space: each is for a single orbital distance within the habitable zone, and a single initial water inventory. "MO_only" files correspond to the concurrent surface magma ocean/runaway greenhouse phase, while "combined_MO_cycling" files correspond to the deep-water cycling period.</p>
Datasets and code for Rapljenović et al. 2024: Adsorption of trace metals onto different plastics during long-term exposure in an estuarine environment: influence of time, stratified water column, and specific surface area
<p>This repository contains datasets and R code to reproduce results from Rapljenović et al. 2024: Adsorption of trace metals onto different plastics during long-term exposure in an estuarine environment: influence of time, stratified water column, and specific surface area.</p>
Time series of Inland Surface Water Dataset in China (ISWDC)
<p>The Inland Surface Water Dataset in China (ISWDC) maps the water body larger than 0.0625 km<sup>2</sup> in the terrestrial land of China for the period 2000–2016, in 8-day temporal and 250 m spatial resolution. It is closely correlated with the national reference data with the determinant coefficients (R<sup>2</sup>) greater than 0.99 in 2000, 2005, and 2010, and possess very good consistency, very similar change dynamics, and similar spatial patterns in different regions with the GSW dataset. The ISWDC data set can be used for studies on the inter-annual and seasonal variation of the surface water systems. It can also be used as reference data for other surface water data set verification and as input parameter for regional and global hydro-climatic models.</p>
Photoelectron spectroscopy data of InP(100) surfaces in contact with water and oxygen
<p>Raw photoelectron spectroscopy data files (XPS and UPS) of InP(100) surfaces before and after adsorption of water and oxygen in ultra-high vacuum. The data was used to produce the graphs in the article M. M. May, H.-J. Lewerenz, and T. Hannappel. “Optical in situ Study of InP(100) Surface Chemistry: Dissociative Adsorption of Water and Oxygen”. <em>Journal of Physical Chemistry C</em> <strong>118</strong>(33) (2014), pp. 19032–19041. <a href="https://doi.org/10.1021/jp502955m">doi:10.1021/jp502955m</a>. Further details can be found in the README.md.</p>
Figure 1 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 1. - Location of the sampling site (star) of flying gurnard Dactylopterus volitans in the Eastern English Channel.
Figure 3 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 3. - Specimen of flying gurnard Dactylopterus volitans (MNHN 2013-0612; 47 cm TL) caught in the Eastern English Channel in 2011.
Figure 2 in Impact of Drought and Land - Use Changes on Surface - Water Quality and Quantity: The Sahelian Paradox
Figure 2. - Whole otolith of flying gurnard (Dactylopterus volitans) with annotation of growth rings (red stars).
Time series of electrical conductivity, temperature and relative stream stage recorded in surface water and streambed sediments of River Erpe and River Gruendlach, Germany
<p><span><a href="../api/records/13336325/draft/files/temp_EC_timeseries.csv/content" target="_blank" rel="noopener noreferrer">temp_EC_timeseries.csv</a></span>: Time series of electrical conductivity (mS cm<sup>-1</sup>), temperature (degC) and relative stream stage (cm) recorded in the surface water and in streambed sediments (depth in cm) of River Erpe and River Gruendlach, Germany.</p> <p> </p> <p><span><a href="../api/records/13336325/draft/files/porewater_ec_timeseries.csv/content" target="_blank" rel="noopener noreferrer">porewater_ec_timeseries.csv</a></span>: Time series of electrical conductivity (mS cm<sup>-1</sup>), temperature (degC), relative stream stage (cm) and total pressure (hPa) recorded in the surface water and in streambed sediments (depth in cm) of River Erpe and River Ammer, Germany, and the Sturt River, South Australia.</p>
FIGURE 7. The typical Tetrapyle octacantha specimens from the surface water from the southern Villefranche-surMer. 1 and 6 in Taxonomy and species diversity of Holocene pylonioid radiolarians from surface sediments of the northeastern Indian Ocean
FIGURE 7. The typical Tetrapyle octacantha specimens from the surface water from the southern Villefranche-surMer. 1 and 6, Ug-view at Type 2; 2-3 and 8, Pr-view at Type 2; 4-7, Fr-view at Type 2. Scale bar equals 0.1 mm. The arrow marks indicate the major portal-spines.
FIG. 7. — Dendrograms resulting from Q in Micropaleontological parameters as proxies of late Miocene surface water properties and paleoclimate in Gavdos Island, eastern Mediterranean
FIG. 7. — Dendrograms resulting from Q-mode cluster analysis and the assemblages identified in each section.
FIG. 5 in Micropaleontological parameters as proxies of late Miocene surface water properties and paleoclimate in Gavdos Island, eastern Mediterranean
FIG. 5. — Relative frequency curves of the planktonic foraminifera identified in Bo Section. Refer to Figure 2 for the explanation of the lithostratigraphical column.
FIG. 3 in Micropaleontological parameters as proxies of late Miocene surface water properties and paleoclimate in Gavdos Island, eastern Mediterranean
FIG. 3. — Relative frequency curves of the planktonic foraminifera identified in Ag. Giannis Section. Refer to Figure 2 for the explanation of the lithostratigraphical column.
FIG. 2 in Micropaleontological parameters as proxies of late Miocene surface water properties and paleoclimate in Gavdos Island, eastern Mediterranean
FIG. 2. — Lithostratigraphical columns of the Ag. Giannis, Potamos and Bo sections, Gavdos Island, Greece.
FIG. 4 in Micropaleontological parameters as proxies of late Miocene surface water properties and paleoclimate in Gavdos Island, eastern Mediterranean
FIG. 4. — Relative frequency curves of the planktonic foraminifera identified in Potamos Section. Refer to Figure 2 for the explanation of the lithostratigraphical column.
Storage experiment for the analysis of dissolved organic matter in surface water and groundwater
<p>This dataset contains the data resulting from a storage experiment, whereby samples from surface water (<em>n</em>=3) and groundwater (<em>n</em>=1) were stored cooled (4°C) or frozen (-20°C) and analysed after 1, 2, 3, 7, 14, 30 and 90 days using fluorescence spectroscopy (Aqualog, Horiba Scientific, Edison, NJ, USA). For each sample, the absorbance spectrum (240–500 nm) and a fluorescence excitation-emission matrix (EEM) were obtained. EEMs were obtained for excitation wavelengths 240–500 nm (3 nm interval) and emission wavelengths 248–825 nm (~4.6 nm interval) with an integration time of 1 second. Five absorbance indicators and eight fluorescence indicators were calculated. The DOC concentration was estimated using the two-wavelength approach of Cook et al. (2017).</p> <p>The dataset consists of four files:</p> <ul> <li>Aqualog data processing and index calculation.R: R script with the code to process the Aqualog data and to calculate the indices.</li> <li>Aqualog.zip: Raw data obtained from the Aqualog, divided into subfolders corresponding to the day of measurement. For each sample, the absorbance spectrum (*ABS.dat) and EEMs of the sample (*SEM.dat) and corresponding blank measurement (*BEM.dat) are provided.</li> <li>Indices.xlsx: Table with index values for all samples.</li> <li>Samples.xlsx: Table with information about all samples (e.g. sampling site, storage duration, storage method)</li> </ul> <p>The geolocations of the sampling sites are:</p> <ul> <li>Site 102 - 50° 29' 6.09''N - 8° 33' 33.57''E</li> <li>Site 134 - 50° 28' 36.55''N - 8° 32' 39.56''E</li> <li>Site 175 - 50° 28' 34.05''N - 8° 32' 42.89''E</li> <li>Site 187 - 50° 28' 49.98''N - 8° 32' 35.12''E</li> </ul>
Hydraulic mixing cell simulation of sources of surface water in the Weierbach catchment
<p>The dataset contains the meteorological forcing data and results of the hydraulic mixing cell (HMC) simulation presented and discussed in the research article: </p> <p><em>Sources of surface water in space and time: Identification of delivery processes and geographical sources with hydraulic mixing-cell modeling</em> (DOI:10.1029/2021WR030332)</p> <p>The simulation was performed with the model HydroGeoSphere and the HMC modelling was used to identify the delivery processes and geographical sources of surface water at specific points of interest (POI) within the riparian-stream continuum of the Weierbach catchment (Luxembourg). Detailed information on the model setup, the location of the POIs, the considered source types and source areas, and the processing we applied to the raw simulation output is given in the research article.</p>
A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015
<p><strong>1. Summary</strong></p> <p>The Congo basin’s Surface Water Storage (SWS) datasets are generated by Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Frederic Frappart, Stephane Calmant, Omid Elmi, Ayan Santos Fleischmann, Melanie Becker, Mohammad J. Tourian, Rômulo A. Jucá Oliveira, Sly Wongchuig in the article entitled "A long-term monthly surface water storage dataset for the Congo basin from 1992 to 2015", <strong><em>Earth System Science Data (submitted)</em></strong>.</p> <p>The dataset was generated using two methods, one based on a multi-satellite approach and one on a hypsometric curve approach. The multi-satellite approach consists of the combination of surface water extent (SWE) from the Global Inundation Extent from Multi-satellite (GIEMS-2) and satellite-derived surface water height (SWH) from radar altimetry (long-term series ERS-2_ENV_SRL) on the same period of availability for the two datasets, here 1995-2015. The hypsometric curve approach consists of the combination of SWE from GIEMS-2 dataset and hypsometric curves obtained from various digital elevation models (DEMs) (i.e., ASTER, ALOS, MERIT, and FABDEM). Both methods estimate monthly spatio-temporal variations of SWS changes across the entire Congo River basin.</p> <p><strong>2. Name Description</strong></p> <ul> <li>HYPSO_XX: hypsometric curve providing the surface water extent area-elevation relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>HYPSO_CORR_XX: corrected hypsometric curve providing the surface water extent area-elevation relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>AREA_STOR_XX: hypsometric curve providing the surface water extent area-storage relationship from XX (where XX stands for ASTER, ALOS, MERIT, and FABDEM DEMs).</li> <li>SWS_XX: monthly surface water storage variations from XX (where XX stands for ASTER, ALOS, MERIT, FABDEM DEMs, and Multi-satellite approach).</li> </ul> <p><strong>3. File Description </strong></p> <p>The SWS estimates from the multi-satellite approach (1995-2015), as well as the hypsometric curves providing the surface water extent area-elevation relationship from the four DEMs (before and after the corrections), the surface water extent area-storage relationship, along with the four SWS estimates (1992-2005).</p> <p>The dataset is gridded on equal-area of 0.25° spatial resolution at the equator, each pixel covers almost 773 km². The reference point for calculating the volume variation is the minimum of surface water extent for each pixel.</p> <p>The files are organized in matrix:</p> <ul> <li><strong>First column</strong> represents the latitude in degree.</li> <li><strong>Second column</strong> represents the longitude in degree.</li> <li><strong>From the third column</strong>: data. In case of hypsometric curve, the data represents elevation in meter on 101 columns representing the increment of 1% flooding in each 773 km<sup>2</sup> pixel from GIEMS-2. In case of SWS data (in km³), there are 288 (respectively 252) columns representing each month of the period over 1992-2015 (respectively 1995-2015) from hypsometric curve approach (respectively multi-satellite approach).</li> </ul>
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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)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.