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”
Pressure and Inertial sensing drifter data for glacial hydrology flow path.
<p>Raw data for paper titled 'Topology and pressure distribution reconstruction of an englacial channel'</p> <p>The dataset consists of field measurements conducted on Austre Brøggerbreen, Ny-Ålesund, Svalbard. The dataset consists of:</p> <p>(1)Raw englacial data (6 deployments), 2019; (2) Raw supraglacial data (11 deployments), 2019; (3) Average GNSS drifter path along the supraglacial channel, 2019; (4) GNSS drifter path along the englacial channel, 2020; (5) Englacial river mapped from a satellite image.</p> <p>The experimental work was conducted between 30.06.2019 and 05.07.2019, during the period of the main spring snow melt. All drifters were recovered by hand from the river.</p>
Data from: The roots of the drought: hydrology and water uptake strategies mediate forest-wide demographic response to precipitation
Drought-induced tree mortality is expected to increase globally due to climate change, with profound implications for forest composition, function and global climate feedbacks. How drought is experienced by different species is thought to depend fundamentally on where they access water vertically below ground, but this remains untracked so far due to the difficulty of measuring water availability at depths at which plants access water (few to several tens of meters), the broad temporal scales at which droughts at those depths unfold (seasonal to decadal), and the difficulty in linking these patterns to forest-wide species-specific demographic responses. We address this problem through a new eco-hydrological framework: we used a hydrological model to estimate belowground water availability by depth over a period of two decades that included a multi-year drought. Given this water availability scenario and 20yr long-records of species-specific growth patterns, we inversely estimated the relative depths at which 12 common species in the forest accessed water via a model of water-stress. Finally, we tested whether our estimates of species relative uptake depths predicted mortality in multi-year drought. The hydrological model revealed clear belowground niches as precipitation was decoupled from water availability by depth at multi-annual scale. Species partitioned the hydrological niche by diverging in their uptake depths and so in the same forest stand, different species experienced very different drought patterns, resulting in clear differences in species-specific growth. Finally, species relative water uptake depths predicted species mortality patterns after the multi-year drought. Species that our method ranked as relying on deeper water were the ones that had suffered from greater mortality, as the zone from which they access water took longer to recharge after depletion. This research changes our understanding of how hydrological niches operate for trees with a trade-off between realized growth potential and survival under drought with decadal scale return time. The eco-hydrological framework highlights the importance of species-specific below ground strategies in predicting forest response to drought. Applying this framework more broadly may help us better understand species-coexistence in diverse forest communities and improve mechanistic predictions of forests productivity and compositional change under future climate.
Data from: Spatial transitions in tree cover are associated with soil hydrology, but not with grass biomass, fire frequency, or herbivore biomass in Serengeti savannahs
1. Although there is a well-known association between tree cover and soil texture in savannahs, the hydrological drivers of tree cover variation have not been systematically explored, particularly in parallel with factors such as fire, herbivory, and tree-grass interactions. The relationship between hydrological factors and tree cover is important for resolving the relative contribution of bottom-up vs. top-down factors in structuring savannah vegetation. 2. We quantified soil moisture dynamics across eight 1-km transects spanning tree cover gradients from open to woody savannah in Serengeti National Park in Tanzania using soil moisture sensors coupled with dataloggers. We mapped tree cover at two spatial scales through supervised classification of high-resolution satellite imagery. We simultaneously produced water retention curves in open and woody habitats within each transect to compare soil hydrological properties and to convert volumetric water content (θ) from dataloggers to plant-available water over the course of an annual cycle. We also quantified grass biomass at 100 locations per transect, estimated fire frequency from MODIS satellite data, and quantified herbivore occupancy with paired camera traps situated in open and woody habitats within each transect. 3. We found a positive relationship between tree cover and soil moisture drainage rate, and found that open habitats had more negative water potentials than woody habitats for a given value of θ. In contrast, we found no evidence for a consistent relationship between grass biomass or fire frequency and tree cover. We found evidence for higher browser occupancy in woody than open habitats, but no habitat effects on herbivores as a group (browsers plus grazers), suggesting that herbivory is unlikely to be the dominant factor explaining variation in tree cover. 4. Our results suggest that variation in tree cover is partly driven by hydrological (edaphic) factors unrelated to fire, herbivory, tree-grass interactions or mean annual precipitation at these spatial scales in Serengeti. We contrast our findings with previous work attributing tree cover shifts in Serengeti to precipitation gradients.
Geospatial and time series dataset for hydrologic analyses within South Asia (GHSA)
<p>Summary of changes:</p> <ul> <li>v2504, GHSA <ul> <li>1,702 stations from 5 countries in South Asia (Bhutan, China, India, Nepal and Pakistan);</li> <li>districts and basin states from 7 countries in South Asia (Afghanistan, Bangladesh, Bhutan, China, India, Nepal and Pakistan)</li> <li>land use change, vegetation index (NDVI, NDVI-crop), precipitation, evaporation (E-total, E-crop and E-irrigation), streamflow, surface and root zone soil moisture, terrestrial water storage change, snow water equivalent and snow cover fraction; 1950-2023</li> <li>publication:</li> </ul> </li> <li>v2409 <ul> <li>test version</li> </ul> </li> <li>v2301, GHI <ul> <li>645 stations, limited to Peninsular India</li> <li>precipitation, evaporation and streamflow; 1950-2020</li> <li>publication: Goteti (2023), Earth Syst. Sci. Data, https://doi.org/10.5194/essd-15-4389-2023</li> </ul> </li> </ul> <p> </p>
Data mining-based machine learning methods for improving hydrological data: a case study of salinity field in the Western Arctic Ocean
<p><span><span>Salinity variations in Arctic Ocean determine the strength of stratification,</span> <span>ocean circulation, and biogeochemical cycles. Therefore, a<span>ccurate </span>salinity product is of great significance for our study of the Arctic Ocean. The mean density structure and wind-driven surface circulation of the Arctic Ocean are largely dominated by the anti-cyclonic Beaufort Gyre in the Canadian Basin, along with the Transpolar Drift<span> (Hall </span><span>et al.,2022)</span>. We focus on the salinity in Western Arctic Ocean. Multiple machine learning methods were used to reconstruct annual salinity product in the Western Arctic Ocean temporal for the period 2003-2022.</span></span></p>
Northern Hemisphere summer insolation and ice volume driven variations in hydrological environment in southwest China
<p>This dataset from a stalagmite record from Chongqing, Southwest China, provides a high-resolution trace element record from the Last Glacial-Interglacial (116.09 to 4.07 ka BP) up to the sub-centennial scale. Line scans of Element/Calcium ratios of the speleothem were measured by laser ablation ICPMS. Chronology is based on 58 U-Th ages.</p>
Pairing Remote Sensing and Clustering in Landscape Hydrology for Large-Scale Changes Identification. Applications to the Subarctic Watershed of the George River (Nunavik, Canada). Dataset and Code.
<p>For remote and vast northern watersheds, hydrological data are often sparse and incomplete. Landscape hydrology provides useful approaches for the indirect assessment of the hydrological characteristics of watersheds through analysis of landscape properties. In this study, we used unsupervised Geographic Object-Based Image Analysis (GeOBIA) paired with the Fuzzy C-Means (FCM) clustering algorithm to produce seven high-resolution territorial classifications of key remotely sensed hydro-geomorphic metrics for the 1985-2019 time-period, each spanning five years. Our study site is the George River watershed (GRW), a 42,000 km<sup>2</sup> watershed located in Nunavik, northern Quebec (Canada). The subwatersheds within the GRW, used as the objects of the GeOBIA, were classified as a function of their hydrological similarities. Classification results for the period 2015-2019 showed that the GRW is composed of two main types of subwatersheds distributed along a latitudinal gradient, which indicates broad-scale differences in hydrological regimes and water balances across the GRW. Six classifications were computed for the period 1985-2014 to investigate past changes in hydrological regime. The seven-classification time series showed a homogenization of subwatershed types associated to increases in vegetation productivity and in water content<br> in soil and vegetation, mostly concentrated in the northern half of the GRW, which were the major changes occurring in the land cover metrics of the GRW. An increase in vegetation productivity likely contributed to an augmentation in evapotranspiration and may be a primary driver of fundamental shifts in the GRW water balance, potentially explaining a measured decline of about 1 % (∼ 0.16 km<sup>3</sup>y<sup>−1</sup>) in the George River’s discharge since the mid-1970s. Permafrost degradation over the study period also likely affected the hydrological regime and water balance of the GRW. However, the shifts in permafrost extent and active layer thickness remain difficult to detect using remote sensing based approaches, particularly in areas of discontinuous and sporadic permafrost.</p>
Interacting impacts of hydrological changes and air temperature warming on lake temperatures highlight the potential for adaptive management: Model output
<p>This archive includes the output from the General Ocean Turbulence Model for a series of simulations that used differing model drivers (inflow discharge, Q, and air temperature, T). The Experiment_output.zip contains text files generated from the GOTM workflow containing modelled water temperatures and the Mod_z.txt are the corresponding depths for these temperatures. </p><p>The file name corresponds to the change made to the driving data from baseline (unchanged conditions), a combination of air temperature <i>increase </i>and flow percentage change e.g. Mod_temp_T_2_Q_1.5 refers to an air temperature increase of 2 degrees Celsius and a flow increase of 50% and a Mod_temp_T_3.5_Q_0.7 refers to an air temperature increase of 3.5 degrees Celsius and a flow decrease of 30%.</p>
Value of water level class observations for parameter set selection in hydrological modelling
<p>Data corresponding to the study "<span>Value of water level class observations for parameter set selection in hydrological modelling</span>", published in the Hydrological Sciences Journal.</p>
Non-Perennial rivers and streams under hydrological stress – comparing the effectiveness of amplicon sequencing and digital microscopy for diatom biodiversity appraisal
<p>ABC is project leader, data collector, contact person, etc.</p>
Oregon hydrologic area agricultural field boundaries and field level and hydrologic unit water use data
<p>The data was developed for the USGS Water-Use and Data Research program grant opportunities G20AS00053 and G21AS00258, combined with fundnig from Oregon Water Resources Department to improve estimates of water use from irrigated lands in Oregon. These data contain attributes of irrigation status, irrigation source type, crop type, irrigation method, assumed irrigation efficiency, irrigation water source, evapotranspiration (ET) data from OpenET, and effective precipitation developed using the USBR ET Demands model. Thee data were aggregated in order to further the development of estimates of applied water at the field-scale.</p>
Hydrologic scenarios of the main Nile tributaries
<p>The water supply model considers four main tributaries to the Nile: Blue Nile, White Nile, Dinder-Rahad and Tekeze-Atbara.</p> <p>Starting from future time series created according to three RCPs scenarios (RCP2.6, RCP4.5 and RCP8.5), a large ensemble of uncertain streamflow is generated by altering the timing and magnitude of extremes (Quinn, J. D., et al. Exploring how changing monsoonal dynamics and human pressures challenge multireservoir management for flood protection, hydropower production, and agricultural water supply. Water Resources Research, 2018, 54.7: 4638-4662). Future streamflows are derived from IPCC 5<sup>th</sup> assessement’s projections of temperature and precipitation using the HBV model and altered by first fitting the monthly means in a Fourier decomposition and then applying perturbations on amplitudes and phases to strengthen the magnitude of extremes and/or their timing.</p> <p>For each combination of tributary and RCP, 100 different realizations of the monthly streamflow of a 94-year-long time series are generated.</p> <p>Data are divided based on tributaries and climatic scenarios. In each file, every row is one of the 100 different realizations of the monthly streamflow time series, while each column contains the monthly streamflow of the river reported in m<sup>3</sup>/s starting from January 2007 in the first column until December 2100 in the last.</p>
Data from: Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance
<p>Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity, and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e., aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e., changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.</p>
Evaluating country-scale irrigation demand through parsimonious agro-hydrological modeling
<p>WaterCROPv2 is an advanced agro-hydrological model designed to estimate irrigation<br>water demand at a national scale by effectively balancing hydrological accuracy with manageable data<br>requirements. Building on the original WaterCROPv1 model, WaterCROPv2 incorporates several<br>significant enhancements, including hourly computation, rainwater canopy interception, soil-dependent5<br>leakage dynamics, and daily evapotranspiration trends based on localized meteorological data.</p> <p>WaterCROPv2 was used to assess mean irrigation water demand for maize from 2005<br>to 2015, illustrating its potential as a decision-support tool for policymakers. </p>
Are deep learning models in hydrology entity aware?
<p>This is the dataset and code accompanying the publication "Are deep learning models in hydrology entity aware?" of Benedikt Heudorfer, Hoshin V. Gupta, and Ralf Loritz to allow reproducible results. </p>
Caravan extension Israel - Israel dataset for large-sample hydrology
<p>Caravan is an open community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world: https://doi.org/10.1038/s41597-023-01975-w; https://zenodo.org/record/6578598. <br>We have employed the published code to derive daily meteorological forcing data and catchment attributes from global data sources to extend Caravan with data for 95 catchments from Israel. </p> <p>For the data processing, the following guide was followed: https://github.com/kratzert/Caravan/wiki/Extending-Caravan-with-new-basins.</p>
Enhancing understanding of the hydrological cycle via pairing of process‐oriented and isotope ratio tracers
<p>This dataset contains monthly average output files from the iCAM6 simulations used in the manuscript "Enhancing understanding of the hydrological cycle via pairing of process-oriented and isotope ratio tracers," in review at the Journal of Advances in Modeling Earth Systems. A file corresponding to each of the tagged and isotopic variables used in this manuscript is included. Files are at 0.9° latitude x 1.25° longitude, and are in NetCDF format. Data from two simulations are included: 1) a simulation where the atmospheric model was "nudged" to ERA5 wind and surface pressure fields, by adding an additional tendency (see section 3.1 of associated manuscript), and 2) a simulation where the atmospheric state was allowed to freely evolve, using only boundary conditions imposed at the surface and top of atmosphere.</p> <p>Specific information about each of the variables provided is located in the "usage notes" section below.</p> <p>Associated article abstract:</p> <p>The hydrologic cycle couples the Earth's energy and carbon budgets through evaporation, moisture transport, and precipitation. Despite a wealth of observations and models, fundamental limitations remain in our capacity to deduce even the most basic properties of the hydrological cycle, including the spatial pattern of the residence time (RT) of water in the atmosphere and the mean distance traveled from evaporation sources to precipitation sinks. Meanwhile, geochemical tracers such as stable water isotope ratios provide a tool to probe hydrological processes, yet their interpretation remains equivocal despite several decades of use. As a result, there is a need for new mechanistic tools that link variations in water isotope ratios to underlying hydrological processes. Here we present a new suite of "process-oriented tags," which we use to explicitly trace hydrological processes within the isotopically enabled Community Atmosphere Model, version 6 (iCAM6). Using these tags, we test the hypotheses that precipitation isotope ratios respond to parcel rainout, variations in atmospheric RT, and preserve information regarding meteorological conditions during evaporation. We present results for a historical simulation from 1980 to 2004, forced with winds from the ERA5 reanalysis. We find strong evidence that precipitation isotope ratios record information about atmospheric rainout and meteorological conditions during evaporation, but little evidence that precipitation isotope ratios vary with water vapor RT. These new tracer methods will enable more robust linkages between observations of isotope ratios in the modern hydrologic cycle or proxies of past terrestrial environments and the environmental processes underlying these observations.<br> </p>
CONTINUUM HYDROLOGICAL MODEL SAMPLE DATA FOR WRF 24 OCTOBER 2021 (APOLLO MEDICANE CASE)
<p>CONTINUUM HYDROLOGICAL MODEL SAMPLE DATA FOR WRF 24 OCTOBER 2021 (APOLLO MEDICANE CASE). Data are ready for publication on MyDewetra platform</p>
A dataset of modeled hydrologic alteration and ecological consequences in stream reaches of the conterminous United States
<p>A dataset of modeled anthropogenically induced hydrologic alteration values for 43 hydrologic indices and modeled losses in native fish biodiversity as a result of streamflow modification, both mapped at the NHDPlus V1 and V2 stream-reach resolution.</p>
Assimilation of NASA's Airborne Snow Observatory snow measurements for improved hydrological modeling: A case study enabled by the coupled LIS/WRF-Hydro system
<p>Data Analysis Scripts and Post-Processed Model Data for a case study using assimilation of ASO Snow Data into the NASA LIS/WRF-Hydro Model. </p> <p>Manuscript Citation:</p> <p>Lahmers T. M., S. V. Kumar, D. Rosen, A. L Dugger, D. Gochis, J. A. Santanello, C. Gangodagamage<sup>,</sup> and R. Dunlap,<strong> </strong>2020: Assimilation of NASA’s Airborne Snow Observatory snow measurements for improved hydrological modeling: A case study enabled by the coupled LIS/WRF-Hydro system,<em>Water Resour. Res.,</em></p>
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.