Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
676
datasets available to search
ShareScore release 0.9.0
Dataset results
676 results for “hydrologic”
The use of GRDC gauging stations for calibrating large-scale hydrological models
<p>The Global Runoff Data Centre provides time series of observed discharges that are very valuable for calibrating and validating the results of hydrological models. We address a common issue in large-scale hydrology which, though investigated several times, has not been satisfactorily solved. Grid-based hydrological models need to fit the reported station location to the river network depending on the resolution, to compare simulated discharge with observed discharge. We introduce an Intersection over Union ratio approach to selected station locations on a coarser grid scale, reducing the errors in assigning stations to the wrong basin. We update the 10-year-old database of watershed boundaries with additional stations based on a high-resolution (3 arcseconds) river network, and we provide source codes and high- and low-resolution watershed boundaries.</p> <p>Same as release on Github: https://github.com/iiasa/CWATM_grdc_calibration_stations/releases/tag/V1.0</p>
Subglacial hydrology modulates basal sliding response of the Antarctic ice sheet to climate forcing
<p><strong><em>Kazmierczak22_data.zip</em></strong><strong> contains the </strong><strong>dataset for the publication </strong><strong>« </strong>Subglacial hydrology modulates basal sliding response of the Antarctic ice sheet to climate forcing » <strong>and </strong><strong>the <em>MATLAB</em> codes used to create the figures appearing in the paper. For more details, please, open the <em>Read me.txt</em> file. </strong></p>
Making the Most out of a Hydrological Model Dataset: Sensitivity Analyses to Open the Model Black-Box (data and code)
<p>This is "data and code" repository for the Water Resources Research Article 2017WR020401 by Borgonovo et al. (2017): "Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box". Each sub-directory contains the Matlab or R scripts to reproduce all paper plots. </p> <p>Note, that the data of this repository (i.e. under ./data_input ) are identical to the data analysed by Rakovec et al. (2014).</p> <p>References:</p> <ul> <li>Borgonovo, E., Lu, X., Plischke, E., Rakovec, O. and Hill, M. C. (2017), Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box. Water Resour. Res.. Accepted Author Manuscript. doi:10.1002/2017WR020767</li> <li>Rakovec, O., M. C. Hill, M. P. Clark, A. H. Weerts, A. J. Teuling, and R. Uijlenhoet (2014), Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models, Water Resour. Res., 50, 409–426, doi:10.1002/2013WR014063.</li> </ul>
Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle
Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October
Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018 in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle
Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018
Fig. 13 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 13: The effect of hydrodynamics inside the Y-Cave, the location behind section B-B' (Fig. 2) at 5.5 m of depth, where the unusually coloured sediment sample was collected for analysis.
Fig. 12 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 12: Limestone tablets from the three representative sites after the 1-year exposure period: A) with bioaccumulation at site 1; B) corroded at site 3; C) abraded at site 6 (Fig. 3, Tab. 1).
Fig. 11 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 11: Cave features: A) stalactites in the chamber with the air pocket (section C-C'); B) submerged stalagmites and flowstones with a lack of marine cave biota (section C-C'); C) submerged scallops (asymmetrical, cuspate, oyster-shell-shaped dissolution depressions in the cave walls used as an indicator of flow direction; Murphy, 2012), (section D-D'); D) corroded cave walls (section F-F').
Fig. 5 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 5: The annual variation of temperature along the Y-Cave (from August 23–27, 2003 to July 4/October 8, 2004). Measurement positions are given in Fig. 3 and depths in Table 1.
Fig. 10 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 10: The mass (m.f.) and volume fractions (v.f.) of four sediment categories in the sediment sample collected behind section B-B' (Fig. 2), at 5.5 m of depth inside the Y-Cave; A) detrital terrigenous sediment>4 mm, B) mixed biogenic and terrigenous detritus, C) shells of gastropod Homalopoma sanguineum, D) other biogenic material – shells, tests and skeletons of other marine organisms.
Fig. 4 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 4: Living communities inside the Y-Cave: A) the entrance part of the cave, vertical wall, depth 9 m, biocenosis of semi-dark caves (GSO, see text for explanation of acronym) dominated by numerous sponge species; B) the entrance part of the cave, ceiling, depth 6 m, GSO dominated by scleractinian coral Leptopsammia pruvoti; C) the entrance part of the cave, overhang, depth 7 m, GSO dominated by scleractinian coral Madracis pharensis; D) the entrance part of the cave, vertical wall (near the bottom), depth 9 m, GSO, a large specimen of the orange sponge Agelas oroides dominates the photo; E) the middle part of the cave, in front of the section C-C', bottom, depth 10 m, a massive white specimen of the sponge Chondrosia reniformis; F) the middle part of the cave, between sections C-C' and D-D', vertical wall and overhang, depth 5 m, the transition from GSO to biocenosis of caves and ducts in total darkness (GO, see text for explanation of acronym), the community is dominated by serpulids; G) the middle part of the cave, between sections C-C' and D-D', vertical wall, depth 5 m, transition from GSO to GO, a dense population of brachiopod Novocrania anomala, encrusting sponge Placospongia decorticans and serpulids; H) the end part of the cave, near the section G-G', vertical wall with overhang and horizontal shelf, depth 6 m, GO with scarce calcareous sponges and serpulids (see Fig. 2 for position of the sections).
Fig. 1 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 1: The non-linear relationship between CO and Ca2+ con2 centrations in H 2O-CO2-CaCO3 solution. Each mixture (e.g. C) of the saturated solutions A and B lies on the straight line between them in the zone of undersaturation with respect to calcite, producing an aggressive solution that dissolves the surrounding carbonate (after Gabrovšek & Dreybrodt (2010)).
Fig. 8 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 8: Temperature, salinity and depth profiles recorded with the CTD probe during a dive inside the Y-Cave (August 27, 2003), 1 – vertical profile at the cave opening; 2 – vertical profile inside the cave entrance part; 3 – vertical profile at the turning point, section C-C'; 4 to 6 – vertical profiles in the inner part of the cave: 4 at approximately section E-E', 5 at approximately section G-G' and 6 at approximately section H-H'.
Fig. 3 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 3: The positions of temperature and light intensity data loggers inside the Y-Cave (dark circles - temperature data loggers; white circles - light intensity data loggers). Four loggers with their photosensitive cell facing upwards are marked with a black dot; the remaining cells were positioned to face the entrance of the cave.
Fig. 9 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 9: Variation of light intensity over a period of 11 days (June 19–30, 2006) at representative sites within the Y-Cave (Fig. 3): logger 1 – the entrance of the cave; logger 4 – the central part of the cave; logger 10 – the innermost part of the cave.
Fig. 6 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 6: The comparison of the tidal (solid line) and temperature (dashed line) fluctuation from February 2–8, 2004. Temperature records are from logger 4 (Fig. 3), and tides from the nearest tide gauge in Zadar port.
Fig. 7 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 7: Vertical temperature profiles inside and outside the YCave taken with the CTD probe (August 27, 2003); the profile labelled with a dotted line was taken at approximately section H-H', the profile labelled with a solid line at approximately section G-G'.
Fig. 2 in Biological response to geochemical and hydrological processes in a shallow submarine cave
Fig. 2: The location, cross-section and layout of the Y-Cave on Dugi Otok Island, Croatia, with characteristic profiles.
Hydrological Station Uttendorf (ÖBB): water gauge measurement
<p>The Austrian Hydrographic Service operates a basic measuring network for recording precipitation, determining flow and water levels in rivers and lakes and monitoring groundwater levels in Austria. This data is organised into precipitation, discharge and groundwater level classes and is accessible via ehyd.gv.at</p>
Fig. 6 in Assessment of sábalo (Prochilodus lineatus) fisheries in the lower Paraná River basin (Argentina) based on hydrological, biological, and fishery indicators
Fig. 6. Sábalo fishery status according to spawning potential ratio (SPR) and fishing mortality (F) variability across time. TRP: Target reference point; LRP: Limit reference point. PS76: Puerto Sánchez 1976; PS02: Puerto Sánchez 2002; V89: Victoria 1989; V94: Victoria 94; V05: Victoria 2005; H05: Helvecia 2005.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.