Process-guided deep learning water temperature predictions: 4c All lakes historical training data

Published by U.S. Geological Survey | Department of the Interior | Metadata Last Checked: January 27, 2026 | Last Modified: 2020-08-20T00:00:00Z

Observed water temperatures from 1980-2018 were compiled for 68 lakes in Minnesota and Wisconsin (USA). These data were used as training data for process-guided deep learning models and deep learning models, and calibration data for process-based models. The data are formatted as a single csv (comma separated values) file with attributes corresponding to the unique combination of lake identifier, time, and depth. Data came from a variety of sources, including the Water Quality Portal, the North Temperate Lakes Long-Term Ecological Research Project, and digitized temperature records from the MN Department of Natural Resources.

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MN Minnesota US USGS:5d8a47bce4b0c4f70d0ae61f United States WI Wisconsin biota climate change deep learning environment hybrid modeling inlandWaters machine learning modeling reservoirs temperate lakes temperature thermal profiles water

Complete Metadata

bureauCode	[ "010:12" ]
identifier	http://datainventory.doi.gov/id/dataset/USGS_5d8a47bce4b0c4f70d0ae61f
spatial	-94.2609062307949, 42.5692312672573, -87.9475441739278, 48.6427837911633
theme	[ "Geospatial" ]

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