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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
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
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
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
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
Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin: 1) Waterbody information for 70 river reaches and 2 reservoirs
Department of the Interior —
This section provides spatial data files that describe the river and reservoirs in the Delaware River Basin included in this release. One shapefile of polylines... -
Federal
Data to support water quality modeling efforts in the Delaware River Basin: 3) Model Driver Data
Department of the Interior —
This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning... -
Federal
Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin
Department of the Interior —
This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture... -
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
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
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
Predicting water temperature in the Delaware River Basin
Department of the Interior —
Daily temperature predictions in the Delaware River Basin (DRB) can inform decision makers who can use cold-water reservoir releases to maintain thermal habitat for... -
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
Stream temperature predictions in the Delaware River Basin using pseudo-prospective learning and physical simulations
Department of the Interior —
Stream networks with reservoirs provide a particularly hard modeling challenge because reservoirs can decouple physical processes (e.g., water temperature dynamics in... -
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
Data to support water quality modeling efforts in the Delaware River Basin
Department of the Interior —
This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning... -
Federal
Data to support water quality modeling efforts in the Delaware River Basin: 1) Spatial data for rivers, reservoirs, and monitoring locations
Department of the Interior —
This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning... -
Federal
Data to support water quality modeling efforts in the Delaware River Basin: 2) River and Reservoir Observations
Department of the Interior —
This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning... -
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
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...