105 datasets found
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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
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
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
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
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
Process-guided deep learning water temperature predictions: 1 Spatial data (GIS polygons for 68 lakes)
Department of the Interior —
This dataset provides shapefile of outlines of the 68 lakes where temperature was modeled as part of this study. The format is a shapefile for all lakes combined... -
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
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
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 2 Water temperature observations
Department of the Interior —
Observed water temperatures from 1980-2018 were compiled for 877 lakes in Minnesota (USA). There were four lakes included in this data release that did not have... -
Federal
Data and model code used to evaluate a process-guided deep learning approach for in-stream dissolved oxygen prediction
Department of the Interior —
This model archive contains data and code used to assess the use of process-informed multi-task deep learning models for predicting in-stream dissolved oxygen... -
Federal
1. Model code for model archive: Identifying structural priors in a hybrid differentiable model for stream water temperature modeling
Department of the Interior —
This section provides model code described by Rahmani et al. (2023b). This code accepts basin attributes and forcings and predicts stream temperatures using a... -
Federal
Walleye Thermal Optical Habitat Area (TOHA) of selected Minnesota lakes: 1 Lake information for 881 lakes
Department of the Interior —
This dataset provides shapefile outlines of the 881 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp,... -
Federal
Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022)
Department of the Interior —
This item contains data and code used in experiments that produced the results for Sadler et. al (2022) (see below for full reference). We ran five experiments for... -
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
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
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
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
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
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...
105 datasets found