Enhanced Runoff Modeling by Incorporating Information from the GR4J Hydrological Model and Multiple Remotely Sensed Precipitation Datasets
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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In: Mo, C.; Su, Q.; Lei, X.; Ma, R.; Huang, Y. et al.: Enhanced Runoff Modeling by Incorporating Information from the GR4J Hydrological Model and Multiple Remotely Sensed Precipitation Datasets. In: Water 16 (2024), Nr. 4, 530. DOI: https://doi.org/10.3390/w16040530
- Ereignis
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Veröffentlichung
- (wo)
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Hannover
- (wer)
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Gottfried Wilhelm Leibniz Universität Hannover
- (wann)
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2024
- Ereignis
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Veröffentlichung
- (wo)
-
Hannover
- (wer)
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Technische Informationsbibliothek (TIB)
- (wann)
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2024
- Urheber
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Mo, Chongxun
Su, Qihua
Lei, Xingbi
Ma, Rongyong
Huang, Yi
Feng, Chengxin
Sun, Guikai
- DOI
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10.15488/16735
- URN
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urn:nbn:de:101:1-2024032801413266281950
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 11:03 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
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Beteiligte
- Mo, Chongxun
- Su, Qihua
- Lei, Xingbi
- Ma, Rongyong
- Huang, Yi
- Feng, Chengxin
- Sun, Guikai
- Gottfried Wilhelm Leibniz Universität Hannover
- Technische Informationsbibliothek (TIB)
Entstanden
- 2024
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