53 datasets found
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Federal
Process-guided deep learning water temperature predictions: 4c All lakes historical training data
Department of the Interior —
Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep... -
Federal
Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation
Department of the Interior —
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that made real-time predictions in the Delaware River... -
Federal
Process-based water temperature predictions in the Midwest US: 6 Habitat metrics
Department of the Interior —
This dataset summarized a collection of annual thermal metrics to characterize lake temperature impacts on fish habitat for 7,150 lakes from uncalibrated models (PB0)... -
Federal
Process-guided deep learning water temperature predictions: 2 Model configurations (lake metadata and parameter values)
Department of the Interior —
This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file... -
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)... -
Federal
Process-guided deep learning water temperature predictions: 6b Sparkling Lake detailed evaluation data
Department of the Interior —
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Sparkling Lake, WI and discrete (manually sampled) water temperature... -
Federal
Process-based water temperature predictions in the Midwest US: 3 Temperature observations
Department of the Interior —
Observed water temperatures from 1980-2019 were compiled for 5,584 lakes in Minnesota and Wisconsin (USA). A subset of these data were used as calibration for... -
Federal
Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin: 2) model driver data
Department of the Interior —
This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the... -
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
Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs
Department of the Interior —
This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017)... -
Federal
Data release: Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes
Department of the Interior —
Climate change and land use change have been shown to influence lake temperatures and water clarity in different ways. To better understand the diversity of lake... -
Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 4 Model inputs (meteorological inputs, clarity, and ice flags)
Department of the Interior —
This dataset includes model inputs (specifically, weather, water clarity, and flags for predicted ice-cover) and is part of a larger data release of lake temperature... -
Federal
Predicting water temperature in the Delaware River Basin: 3 Model configurations
Department of the Interior —
This dataset includes model parameters and metadata used to configure models. -
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
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
Process-guided deep learning water temperature predictions: 6a Lake Mendota detailed evaluation data
Department of the Interior —
This dataset includes "test data" compiled water temperature data from an instrumented buoy on Lake Mendota, WI and discrete (manually sampled) water temperature... -
Federal
Process-guided deep learning water temperature predictions: 3a Lake Mendota inputs
Department of the Interior —
This dataset includes model inputs that describe local weather conditions for Lake Mendota, WI. Weather data comes from two sources: locally measured (2009-2017) and... -
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
Model predictions for heterogeneous stream-reservoir graph networks with data assimilation
Department of the Interior —
This data release provides the predictions from stream temperature models described in Chen et al. 2021. Briefly, various deep learning and process-guided deep... -
Federal
Process-guided deep learning water temperature predictions: 6 Model evaluation (test data and RMSE)
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)...
53 datasets found