Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 5 Model predictions

Published by U.S. Geological Survey | Department of the Interior | Metadata Last Checked: January 27, 2026 | Last Modified: 2020-12-09T00:00:00Z

<p>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.</p>

Find Related Datasets

Click any tag below to search for similar datasets

AL Alabama DE Delaware GA Georgia IA ID Idaho Iowa KS Kansas MA MD ME MI MS Maine Maryland Massachusetts Michigan Mississippi NC NJ NM NV NY Nevada New Jersey New Mexico New York North Carolina OH OK OR Ohio Oklahoma Oregon PA Pennsylvania RI Rhode Island SC South Carolina TN TX Tennessee Texas US USGS:5f9865e5d34e198cb77ff08a UT United States Utah VA Virginia WA WI WV WY Washington West Virginia Wisconsin Wyoming deep learning environment inlandWaters machine learning modeling streams water resources water temperature

Complete Metadata

bureauCode	[ "010:12" ]
identifier	http://datainventory.doi.gov/id/dataset/USGS_5f9865e5d34e198cb77ff08a
spatial	-123.32988684, 30.1454932, -70.97964444, 48.90595739
theme	[ "Geospatial" ]

2 resources available

Location