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Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models.

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Title: Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models.
Authors: Muñoz, David F.1,2 (AUTHOR) davidmunozpauta@vt.edu, Moftakhari, Hamed1,3 (AUTHOR), Moradkhani, Hamid1,3 (AUTHOR)
Source: Hydrology & Earth System Sciences. 2024, Vol. 28 Issue 11, p2531-2553. 23p.
Database: Environment Complete
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Header DbId: eih
DbLabel: Environment Complete
An: 178007176
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models.
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  Data: <searchLink fieldCode="JN" term="%22Hydrology+%26+Earth+System+Sciences%22">Hydrology & Earth System Sciences</searchLink>. 2024, Vol. 28 Issue 11, p2531-2553. 23p.
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.5194/hess-28-2531-2024
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      – Code: eng
        Text: English
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        PageCount: 23
        StartPage: 2531
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      – TitleFull: Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models.
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            NameFull: Muñoz, David F.
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            NameFull: Moftakhari, Hamed
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              Text: 2024
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              Value: 28
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              Value: 11
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