Deep Dive into Global Hydrologic Simulations: Harnessing the Power of Deep Learning and Physics-informed Differentiable Models (δHBV-globe1.0-hydroDL)

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Deep Dive into Global Hydrologic Simulations: Harnessing the Power of Deep Learning and Physics-informed Differentiable Models (δHBV-globe1.0-hydroDL) ; day:05 ; month:10 ; year:2023 ; pages:1-23 ; extent:23
Geoscientific model development discussions ; (05.10.2023), 1-23 (gesamt 23)

Creator
Feng, Dapeng
Beck, Hylke
de Bruijn, Jens
Sahu, Reetik Kumar
Satoh, Yusuke
Wada, Yoshihide
Liu, Jiangtao
Pan, Ming
Lawson, Kathryn
Shen, Chaopeng

DOI
10.5194/gmd-2023-190
URN
urn:nbn:de:101:1-2023101204374930630617
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:53 AM CEST

Data provider

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Associated

  • Feng, Dapeng
  • Beck, Hylke
  • de Bruijn, Jens
  • Sahu, Reetik Kumar
  • Satoh, Yusuke
  • Wada, Yoshihide
  • Liu, Jiangtao
  • Pan, Ming
  • Lawson, Kathryn
  • Shen, Chaopeng

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