Enhanced Runoff Modeling by Incorporating Information from the GR4J Hydrological Model and Multiple Remotely Sensed Precipitation Datasets
- 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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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
- Event
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Veröffentlichung
- (where)
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Hannover
- (who)
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Gottfried Wilhelm Leibniz Universität Hannover
- (when)
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2024
- Event
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Veröffentlichung
- (where)
-
Hannover
- (who)
-
Technische Informationsbibliothek (TIB)
- (when)
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2024
- Creator
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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
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 11:03 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Mo, Chongxun
- Su, Qihua
- Lei, Xingbi
- Ma, Rongyong
- Huang, Yi
- Feng, Chengxin
- Sun, Guikai
- Gottfried Wilhelm Leibniz Universität Hannover
- Technische Informationsbibliothek (TIB)
Time of origin
- 2024
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