Representing Anthropogenic Processes in the National Water Model: A Machine Learning Approach to Reservoir Operations

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    W[2018AGUFM.H41P2326F]
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ADS bibcode
2018AGUFM.H41P2326F
year
2018
Listed Authors
Frazier, N.
Rezaeianzadeh, M.
Flowers, T.
Mattern, D.
Ogden, F. L.
Aggett, G. R.
Listed Institutions
NOAA Affiliate, CyberData Technologies, Office of Water Prediction, National Water Center, Tuscaloosa, AL, United States
NOAA Affiliate, Lynker Technologies, Office of Water Prediction, Tuscaloosa, AL, United States
NOAA/NWS Office of Water Prediction, National Water Center, Tuscaloosa, AL, United States
NOAA Affiliate, Lynker Technologies, Office of Water Prediction, Tuscaloosa, AL, United States
NOAA Affiliate, University Corporation for Atmospheric Research, Office of Water Prediction, National Water Center, Tuscaloosa, AL, United States
AMEC Earth and Environmental, Boulder, CO, United States

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