Representing Anthropogenic Processes in the National Water Model: A Machine Learning Approach to Reservoir Operations
- 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
Linked Authors [?]
Linked Institutions