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Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 3 Model inputs

Dates

Publication Date
Start Date
2010-10-01
End Date
2016-09-30

Citation

Rahmani, F., Lawson, K., Ouyang, W., Appling, A.P., Oliver, S.K., and Shen, C., 2020, Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: U.S. Geological Survey data release, https://doi.org/10.5066/P97CGHZH.

Summary

This data release component contains model inputs including river basin attributes, weather forcing data, and simulated and observed river discharge.

Contacts

Attached Files

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03_inputs.xml
Original FGDC Metadata

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34.41 KB application/fgdc+xml
AT_basin_attributes.csv 22.75 KB text/csv
obs_discharge.csv 6.06 MB text/csv
pred_discharge.csv 3.16 MB text/csv
weather_drivers.zip 3.95 MB application/zip

Purpose

Decision support, water quality research, and advancement of machine learning in hydrology

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