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Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data: 2 Observations

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 mean daily stream water temperature observations, retrieved from the USGS National Water Information System (NWIS) and used to train and validate all temperature models. The model training period was from 2010-10-01 to 2014-09-30, and the test period was from 2014-10-01 to 2016-09-30.

Contacts

Attached Files

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temperature_observations.csv 5.51 MB text/csv

Purpose

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

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