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Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 7 thermal and optical habitat estimates
Department of the Interior —
Using predicted lake temperatures from uncalibrated, process-based models (PB0) and process-guided deep learning models (PGDL), this dataset summarized a collection... -
Federal
Model code, outputs, and supporting data for approaches to process-guided deep learning for groundwater-influenced stream temperature predictions
Department of the Interior —
This model archive provides all data, code, and modeling results used in Barclay and others (2023) to assess the ability of process-guided deep learning stream... -
Federal
Daily water column temperature predictions for thousands of Midwest U.S. lakes between 1979-2022 and under future climate scenarios
Department of the Interior —
Lake temperature is an important environmental metric for understanding habitat suitability for many freshwater species and is especially useful when temperatures are... -
Federal
Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin
Department of the Interior —
Daily maximum water temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions
Department of the Interior —
This data release component contains water temperature predictions in 118 river catchments across the U.S. Predictions are from the four models described by Rahmani... -
Federal
Predicting water temperature in the Delaware River Basin: 5 Model prediction data
Department of the Interior —
Several models were used to improve water temperature prediction in the Delaware River Basin. PRMS-SNTemp was used to predict daily temperatures at 456 stream reaches... -
Federal
Process-guided deep learning water temperature predictions: 3 Model inputs (meteorological inputs and ice flags)
Department of the Interior —
This dataset includes model inputs (specifically, weather and flags for predicted ice-cover) and is part of a larger data release of lake temperature model inputs and... -
Federal
Data-Driven Drought Prediction Project Model Outputs: Daily Streamflow and Streamflow Percentile Predictions for the Colorado River Basin Region
Department of the Interior —
This metadata record describes outputs from 12 configurations of long short-term memory (LSTM) models which were used to predict streamflow drought occurrence at 384... -
Federal
Process-guided deep learning water temperature predictions: 5 Model prediction data
Department of the Interior —
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin.... -
Federal
Predicting water temperature in the Delaware River Basin: 2 Water temperature and flow observations
Department of the Interior —
Observations related to water and thermal budgets in the Delaware River Basin. Data from reservoirs in the basin include reservoir characteristics (e.g., bathymetry),... -
Federal
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations
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
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions
Department of the Interior —
This data release component contains water temperature predictions in 118 river catchments across the U.S. Predictions are from the four models described by Rahmani... -
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
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. (2020). -
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. (2020). -
Federal
A deep learning model and associated data to support understanding and simulation of salinity dynamics in Delaware Bay
Department of the Interior —
Salinity dynamics in the Delaware Bay estuary are a critical water quality concern as elevated salinity can damage infrastructure and threaten drinking water... -
Federal
Deep learning classification of landforms from lidar-derived elevation models in the glaciated portion of the northern Delaware River Basin of New Jersey, New York, and Pennsylvania
Department of the Interior —
The Delaware River Basin (DRB) covers portions of five states (Delaware, Maryland, New Jersey, New York, and Pennsylvania) and several geologic provinces,... -
Federal
Data release: Process-guided deep learning predictions of lake water temperature
Department of the Interior —
Climate change has been shown to influence lake temperatures in different ways. To better understand the diversity of lake responses to climate change and give... -
Federal
Data and model code in support of Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites, Insights from deep learning
Department of the Interior —
We developed a suite of models using deep learning to make hindcast predictions of the 7-day average backward-looking nitrate concentration at 46 predominantly... -
Federal
Process-guided deep learning water temperature predictions: 6c All lakes historical evaluation data
Department of the Interior —
This dataset includes evaluation data ("test" data) and performance metrics for water temperature predictions from multiple modeling frameworks. Process-Based (PB)...