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Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: 2 Water temperature observations

Dates

Release Date
2020-10-30
Start Date
1980-04-01
End Date
2019-12-31

Citation

Willard, J., Read, J.S., Appling, A.P., and Oliver, S.K., 2020, Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning: U.S. Geological Survey data release, https://doi.org/10.5066/P9I00WFR.

Summary

Observed water temperatures from 1980-2019 were compiled for 2,332 lakes in the US. These data were used as training, test, and error-estimation data for process-guided deep learning models and the evaluation of 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. This dataset is part of a larger data release of lake temperature model inputs and outputs for these same lakes (https://doi.org/10.5066/P9I00WFR).

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Attached Files

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5ebe566a82ce476925e44b29.xml
Original FGDC Metadata

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13.56 KB application/fgdc+xml
temperature_observations.zip 7.35 MB application/zip

Purpose

Fisheries biology, limnological research, and climate science.

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