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 GAGES-II dataset as a test case for temperature prediction using deep learning methods. The associated manuscript explores the value of including stream discharge as a predictor in the temperature models, including the value of predicted discharge from a separate model when no discharge measurements are available.
The data are organized into these items:
- Spatial Information - Locations of the 118 monitoring sites used in this study
- Observations - Water temperature observations for the 118 sites used in this study
- Model Inputs - Model inputs, including basin attributes, weather drivers, and discharge
- Models - Code and configurations for the stream temperature models
- Model Predictions - Predictions of stream water temperature
- Model Evaluation - Performance metrics for each stream temperature model
This research was funded by the Integrated Water Prediction Program at the US Geological Survey.