Wenyu Ouyang

7 items:

Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge. Categories: Data; Tags: AL, Alabama, DE, Delaware, GA, All tags...
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions 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 et al. (2020): locally-fitted linear regression, LSTM-noQ, LSTM-obsQ, and LSTM-simQ. Categories: Data; Tags: AL, Alabama, DE, Delaware, GA, All tags...
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 1 Spatial information 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).<\p> Tags: AL, Alabama, DE, Delaware, GA, All tags...
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 4 Models This data release component contains model code and configurations for the LSTM and linear regression models used to predict stream temperature. Tags: AL, Alabama, DE, Delaware, GA, All tags...
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 6 Model evaluation This data release component contains evaluation metrics used to assess the predictive performance of each stream temperature model. For further description, see the metric calculations in the supplement of Rahmani et al. (2020), equations S1-S7. Categories: Data; Tags: AL, Alabama, DE, Delaware, GA, All tags...

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