Machine learning for postprocessing ensemble streamflow forecasts
Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles, distributed hydrological model, and machine learning to generate ensemble streamflow forecasts at medium-range lead times (1–7 days). We demonstrat...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IWA Publishing
2023-01-01
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| Series: | Journal of Hydroinformatics |
| Subjects: | |
| Online Access: | http://jhydro.iwaponline.com/content/25/1/126 |