26 datasets found
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Federal
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
5 Model Predictions: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release item contains water temperature predictions for 455 river sites across the U.S. Predictions are from the models described by Rahmani et al. (2021b). -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs
Department of the Interior —
This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge. -
Federal
4 Model Code: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release component contains model code and configurations for the LSTM models used to predict stream temperature. -
Federal
1 m digital bathymetric contours from NOAA charts as organized for the Long Island Sound Study Geographic Information System (LISSGIS) library (LISBATHY.SHP)
Department of the Interior —
The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of... -
Federal
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
1 m Digital Bathymetric Contours from NOAA Charts as Organized for the LISSGIS Library (LISBATHY)
Department of the Interior —
The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of... -
Federal
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 4 Models
Department of the Interior —
This data release component contains model code and configurations for the LSTM and linear regression models used to predict stream temperature. -
Federal
2 Observations: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release component contains mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to... -
Federal
ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data
Department of the Interior —
This data release provides all data and code used in Rahmani et al. (2020) to model stream temperature and assess results. Briefly, we used a subset of the USGS... -
Federal
3 Model Forcings: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge. -
Federal
Development: Development delineation: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 1 Spatial information
Department of the Interior —
This data release component contains a shapefile of monitoring site locations coincident with the outlets of the 118 river basins modeled by Rahmani et al.... -
Federal
1 Site Information: Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release component contains shapefiles of river basin polygons and monitoring site locations coincident with the outlets of those basins. A table of basin... -
Federal
Deep learning approaches for improving prediction of daily stream temperature in data-scarce, unmonitored, and dammed basins
Department of the Interior —
This data release provides all data and code used in Rahmani et al. (2021b) to model stream temperature and assess results. Briefly, we modeled stream temperature at... -
Federal
DisOcean: Distance to the ocean: Rhode Island National Wildlife Refuge, RI, 2014
Department of the Interior —
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of... -
Federal
Compilation of multi-agency water temperature observations for U.S. streams, 1894-2022
Department of the Interior —
This data release collates stream water temperature observations from across the United States from four data sources: The U.S. Geological Survey's National Water... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 6 Model evaluation
Department of the Interior —
This data release component contains evaluation metrics used to assess the predictive performance of each stream temperature model. For further description, see the...
26 datasets found