CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Abstract - 0.06 to 0.18 over the CONUS (contiguous US). Third, with the lake module incorporated, the NSE score is further improved by 56.2 % and the systematic bias is reduced by 17 %. Lastly, over 20 % of the false alarms on 2-year floods in the US can be mitigated with the lake module enabled, at the expense of only missing 2.3 % more events. This study demonstrated the advantages of the proposed hydrological modeling framework, which could provide a solid basis for continental- and global-scale water modeling at fine resolution. Furthermore, the use of ensemble forecasts can be incorporated into this framework; and thus, optimized streamflow prediction with quantified uncertainty information can be achieved in an operational fashion for stakeholders and decision-makers.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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CREST-VEC: a framework towards more accurate and realistic flood simulation across scales ; volume:15 ; number:15 ; year:2022 ; pages:6181-6196 ; extent:16
Geoscientific model development ; 15, Heft 15 (2022), 6181-6196 (gesamt 16)
- Creator
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Li, Zhi
Gao, Shang
Chen, Mengye
Gourley, Jonathan
Mizukami, Naoki
Hong, Yang
- DOI
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10.5194/gmd-15-6181-2022
- URN
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urn:nbn:de:101:1-2022081105173840191382
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:35 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Li, Zhi
- Gao, Shang
- Chen, Mengye
- Gourley, Jonathan
- Mizukami, Naoki
- Hong, Yang