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.
1,188
datasets available to search
ShareScore release 0.9.0
Dataset results
1,188 results for “DELTA”
Delta-X: Delft3D Sediment Model, Site 399, Terrebonne Basin, MRD, Louisiana, USA
This dataset contains the Delft3D model of the intensive site 399 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF format.
Pre-Delta-X: River Discharge Channel Surveys across Atchafalaya Basin, LA, USA, 2016
This dataset provides river discharge measurements collected at selected locations across the Atchafalaya River Basin, within the Mississippi River Delta (MRD) floodplain in coastal Louisiana, USA. The measurements were made during the Pre-Delta-X campaign on October 15 to 20, 2016. Seventy-five channel surveys were conducted with a SonTek RiverSurveyor M9 acoustic doppler current profiler (ADCP) on selected wide channels (~100 m) and a few selected (~10 m) narrow channels. ADCP data provide near-instantaneous estimates of river discharge across the sampled channels. Sites coincided with AirSWOT swaths in the Atchafalaya River Basin and water level measurement locations. This in situ dataset was used to calibrate and validate Delta-X hydrodynamic models.
Delta-X: Delft3D Broad-Scale Sediment Model, Terrebonne Basin, MRD, Louisiana, USA
This dataset contains the Delft3D model of the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall campaigns in 2021 and include hydrodynamics, waves, and sediment transport. Bottom friction was calibrated using AirSWOT water elevation data, while sediment parameters were calibrated using AVIRIS-NG Total Suspended Solids (TSS) data. All files required to run the simulations are included. The model's output of water levels, velocity, and depth-averaged sediment concentrations are provided for both campaigns as netCDF files. The dataset includes a netCDF file containing the annual inorganic mass accumulation rates derived through a storms analysis and modelling.
Delta-X: Particulate Organic Carbon Concentration from Water Samples, MRD, LA, 2021
This dataset provides measurements of particulate organic carbon (POC) concentrations made on water samples collected during 2021 in surface waters of the Atchafalaya River and Terrebonne Basins, portions of the Mississippi River Delta in coastal Louisiana. Water samples were collected at ~0.5 m depth from surface during the spring (2021-03-25 to 2021-04-22) and fall (2021-08-14 to 2021-09-24) field efforts. Field sampling was paused on August 25 and resumed on September 13 due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study sites. Water quality changes in this dataset caused by the hurricane are expected to be minimal. Samples were collected in multiple channels of varying width (from a few meters to >100 m) near Delta-X intensive study sites, in open bays and lakes, and a few locations in the nearshore Gulf of Mexico. For each sample, the water sample volume was filtered (in triplicate) through 25-mm glass microfiber (GF/F) filters to retain the suspended particles. The amount of organic carbon retained on each filter was measured using an elemental carbon, hydrogen and nitrogen (CHN) analyzer and normalized by the volume of sample water filtered. The reported values in this dataset include the mean and standard deviation of POC measurements from three replicate samples collected at each site.
ABoVE: Wetland Inundation Coverage at Yukon Flats, AK and PA Delta, Canada, 2017-2019
This dataset provides time series of wetland inundation coverage maps and corresponding inundation frequency maps at ~10-meter resolution estimated every 12 days during the free-water period (May to October) for the years 2017-2019 over the Yukon Flats (YK) portion of the Yukon River, Alaska, USA, and the Peace-Athabasca Delta (PAD), Alberta, Canada. Wetland inundation coverage was determined by a two-step modified decision-tree classification approach that first used Sentinel-1 C-band SAR to identify likely inundated areas across a study site and was followed by a decision-tree classification step with C-band SAR backscatter statistics thresholds to distinguish among different inundation components. The result of this process was five classes for each inundation map, namely Open Water (OW), Floating Plants (FP), Emergent Plants (EP), Flooded Vegetation (FV), and Dry Land (DRY). After all the individual (every 12 days) inundation coverage maps were derived for a study site, they were generalized to two-class maps which maintained only inundation status. These generalized maps were then stacked and summarized to produce the inundation frequency map for the site. In these maps, higher values signify more frequently inundated areas, with the maximum value representing permanently inundated pixels. The Sentinel-1 inundation mapping capability demonstrated here provided frequent, broad-scale mapping of different wetland inundation components. Integration of such products with process-based methane (CH4) models would improve simulation of CH4 emissions from wetlands.
CO2 and CH4 Fluxes from Waterbodies, Yukon-Kuskokwim Delta, Alaska, 2016-2019
This dataset provides estimates of carbon dioxide (CO2) and methane (CH4) diffusive fluxes from waterbodies, and watershed landcover data for the central-interior of the Yukon-Kuskokwim Delta (YK delta), Alaska. Dissolved concentrations of methane and carbon dioxide were predicted using an integrated terrestrial-aquatic approach to scale observations based on landscape and waterbody remote sensing drivers. The observations include ~300 samples of surface water dissolved gases collected in July 2016-2019 from the central region of the YK Delta, Alaska. A machine learning model was used to generate estimated fluxes. Model inputs include Sentinel-2 MSI with derived normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), an Arctic digital elevation model (DEM) with derived slope and flow accumulation, Sentinel-1 C-band July and December VV and VH composites, and a landcover map. Waterbody size, shape, and reflectance were determined using object-based image analysis in Google Earth Engine. Landscape-level input data were averaged in non-nested sub-basins calculated using the System for Automated Geoscientific Analyses (SAGA) "channel network" algorithm at three threshold sizes. Cross validation was used to tune and select variables for gradient boosting models. The trained gradient boosting models were then used to predict dissolved methane and carbon dioxide in all waterbodies (~17,000) in the region. These aquatic concentrations were converted to fluxes using an average gas transfer velocity from observations (0.33 m/d). The data are provided in GeoTIFF and shapefile formats.
SASSIE Arctic Field Campaign Shipboard Delta-18O Data Fall 2022
The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200km of the sea ice edge. This dataset contains delta-18O measurements from sea water and ice. Delta-18O is the ratio of stable isotopes oxygen-18 (18O) and oxygen-16. Water samples were collected from either a GoFlo bottle lowered from the side of the ship, or the outflow of the Salinity Snake. Ice samples (dimension ice_obs) were collected during two ice stations where augur tailings were collected and melted. Data are available in netCDF format.
CMS: LiDAR Data for Mangrove Forests in the Zambezi River Delta, Mozambique, 2014
This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014. The data are arranged into 144 1- by 1-km tiles.
Delta-X: AirSWOT L3 Water Surface Elevations, MRD, Louisiana, 2021, Version 2
This dataset contains water surface elevations at selected point locations generated from the AirSWOT data collected during the Spring and Fall 2021 Delta-X deployments over the Atchafalaya and Terrebonne basins in Louisiana, USA. AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The Level 3 (L3) data were created by masking land areas out of the AirSWOT Level 2 products, then filtering and averaging to the AirSWOT heights to produce water surface elevations at selected points throughout the scene. The AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. AirSWOT performance in the floodplain was limited by the presence of vegetation and the very small slope characteristic of two dimensional floodplain discharge. Therefore, the bulk of the AirSWOT data collections were targeted at the larger channels, since the channel discharge provides the necessary boundary conditions for potential overflow to islands and floodplains. The data are provided in comma-separated values (CSV) format.
Pre-Delta-X: Vegetation Species, Structure, Aboveground Biomass, MRD, LA, USA, 2015
This dataset provides vegetation species, height, stem density and diameter, and species aboveground biomass (AGB) measurements collected at herbaceous and forested wetland sites across the Atchafalaya and Terrebonne basins within the Mississippi River Delta (MRD) floodplain in coastal Louisiana, USA. The measurements were made during the Pre-Delta-X campaign in Spring 2015 and Fall 2015. Vegetation height and density and diameter data are only provided for forested Atchafalaya sites during the spring collections. At the nine herbaceous wetland sites, a transect was established perpendicular to the wetland edge with replicate sample plots (0.25 m2, 5 m apart) located at 50, 100, and 150 m from the wetland edge to capture the range of vegetation structure, zonation, and composition. AGB was harvested inside the duplicate plots at each sampling location. At the six forested wetland sites, duplicate circular plots (10 m radius, 50 m apart) were established inside the forest approximately 30 m from the wetland edge. All trees with a diameter at breast height (DBH at 1.3 m) > 2.5 cm were measured within each plot and identified to species. The height of trees was measured with a laser range finder. AGB was estimated using species-specific allometric equations. Measurements were used to generate marsh and forested wetland coverage and biomass in response to seasonality within both basins. The data will be used to calibrate remote sensing data (e.g., UAVSAR, AVIRIS-NG) and hydrodynamics and sediment transport models.
Pre-Delta-X: Aboveground Biomass and Vegetation Maps, Wax Lake Delta, LA, USA, 2016
This dataset includes aboveground biomass (AGB) and vegetation of herbaceous and forest wetland at 5.4 m resolution across the Wax Lake Delta (WLD) in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Vegetation classes were derived from Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquired over the Atchafalaya Basin and the Terrebonne Basin in October 2016 in combination with a digital elevation model. The AVIRIS-NG surface reflectance data were also combined with L-band Uninhabited Airborne Vehicle Synthetic Aperture Radar (UAVSAR) HV backscatter and scattering component values from coincident vegetation sample sites to develop and test AGB models for emergent herbaceous and forested wetland vegetation. This study used the integrated airborne data from AVIRIS-NG and UAVSAR to assess the instruments' unique capabilities in combination for estimating AGB in coastal deltaic wetlands. The 5.4 m resolution vegetation classification map for the WLD study area was then used to apply the best models to estimate AGB across the WLD.
Pre-Delta-X: UAVSAR Georeferenced Channel Maps, Atchafalaya Basin, LA, USA, 2016, V2
This dataset provides spatial data on water channels in the estuary of the Atchafalaya Basin of the Mississippi River Delta of coastal Louisiana. These Level-3 (L3) channel maps were developed from interferograms derived from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data collected on 2016-10-16 (low tides) and 2016-10-17 (high tides). The channel maps define open water paths in hydrodynamic models and are used to evaluate model performance. This is version 2 of this dataset. Data are provided in cloud optimized GeoTIFF format.
Pre-Delta-X: L3 AirSWOT-derived Water Level Profiles, Wax Lake Outlet, LA, USA, 2015
This dataset contains water level profiles generated from the AirSWOT data collected in the Atchafalaya Basin in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Part of the Pre-Delta-X Campaign, AirSWOT used near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and uncertainty in May 2015. This Level 3 (L3) AirSWOT dataset is in the form of numerous profiles of water level along the Wax Lake Outlet.
Delta-X: Total Suspended Solids Concentration across MRD, LA, USA, 2021, Version 2
This dataset provides measurements of total suspended solids concentrations (TSS) of surface waters in the Atchafalaya River and Terrebonne Basins during the spring (2021-03-25 to 2021-04-22) and fall (2021-08-14 to 2021-09-24) field efforts by the Delta-X project. Field sampling was paused on August 25 and resumed on September 13, 2021, due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study site. Water quality changes caused by the hurricane were expected to be minimal. Samples were collected from ~0.5 m of surface in multiple channels of varying width (from a few meters to >100 m), near Delta-X intensive study sites, in open bays and lakes, and at few locations in the nearshore Gulf of Mexico. For each collection, the water sample volume was filtered, and the suspended particles retained on the filter were weighed after drying. The TSS concentration was calculated as the difference of the filter weight (before and after filtration) divided by the volume filtered.
Delta-X: NUMAR Predictive Model for Marsh Accretion Rates and Chemical Properties
This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments. This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF).
Surface Water Elevation and Quality, Peace-Athabasca Delta, Canada, 2006-2007
The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands. This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California.
Delta-X: Calibrated ANUGA Hydrodynamic Outputs for the Atchafalaya Basin, MRD, LA
This dataset provides ANUGA hydrodynamic modeling results and input run-scripts for the Atchafalaya basin in the Mississippi River Delta in southern Louisiana, USA, during three windows of time corresponding to the Delta-X and Pre-Delta-X field campaigns in fall 2016, spring 2021, and fall 2021. ANUGA is a 2D depth-integrated hydrodynamic model which uses the Finite Volume Method (FVM) to numerically solve the shallow water momentum and continuity equations for fluid flow in broad-scale geophysical systems. Each iteration of the model was extensively calibrated using a database of in-situ and remotely-sensed observations, including about 54 water level gauges, numerous water surface profiles collected by AirSWOT or lidar, and water level change measurements derived from UAVSAR. The model was forced using observational data collected from NOAA and USGS, and the model mesh was specifically designed to capture channel-island connectivity using high-resolution Planet Labs imagery spanning over a decade. In total, over a month of simulation outputs are included in this dataset, covering different seasons and hydrological conditions in the Atchafalaya and Wax Lake Delta systems. These model outputs can be leveraged with other Delta-X datasets to provide contextual information about water levels or flow velocities at different times or locations within the Atchafalaya basin, and the model codes provided can be used to simulate additional time periods for further analysis in this region. Model outputs are presented in NetCDF (*.nc) format and run-scripts are in Python (*.py) or contained in compressed (*.zip) file format.
Delta-X: Land Subsidence Rate, Mississippi River Delta (MRD), Louisiana, USA
This dataset provides estimates of land subsidence rates for the Delta-X domain area within the Atchafalaya and Terrebonne basins for 2021. The study area is a portion of the Mississippi River Delta in coastal Louisiana, U.S. The total subsidence is calculated as the sum of deep and shallow vertical elevation change rates. The deep subsidence rate is based on information from the Coastal Protection and Restoration Authority (CPRA) of Louisiana, documented in the Phase-4 subsidence trend report prepared for and provided by CPRA (2022). The shallow subsidence is calculated for the Delta-X study area by interpolation of publicly available data provided by CPRA for their coast-wide estimation of shallow subsidence in the 2023 Coastal Master Plan. The total subsidence rates and the estimated uncertainty in the total subsidence rates are provided as separate files in cloud optimized GeoTIFF (COG) format at 30-m (0.0003 decimal degrees) resolution.
Pre-Delta-X: L2 AVIRIS-NG Surface Spectral Reflectance across MRD, LA, USA, 2015-2016
This Level 2 (L2) dataset provides surface spectral reflectance data acquired over the Atchafalaya and Terrebonne basins of the Mississippi River Delta (MRD) of coastal Louisiana, USA, in 2015-2016. The data include georectified images with Lambertian-equivalent surface reflectance and composite mosaics with adjustments for Bidirectional Reflectance Distribution Function (BRDF) effects. The imagery was acquired by the Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), as part of the Pre-Delta-X campaign.
Delta-X: NUMAR Soil Accretion Modeled to 2100, MRD, Louisiana, USA
This dataset holds modeled estimates of soil accretion for the Atchafalaya and Terrebonne basins in the Mississippi River Delta of coastal Louisiana, U.S. Soil accretion was predicted from 2021-2100 using the Numerical Understanding of Marsh Accretion Resilience (NUMAR) model. This process-based model is an adaptation of the NUMAN model that was modified for marsh environments. The input parameters were aggregated within ecogeomorphic cells, areas of similar vegetation and elevation. The dataset includes spatially explicit input values, description of important parameters, and a shapefile of model outputs.
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.