Karst spring discharge modeling based on deep learning using spatially distributed input data

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Andreas Wunsch - , Karlsruhe Institute of Technology (First author)
  • Tanja Liesch - , Karlsruhe Institute of Technology (Author)
  • Guillaume Cinkus - , Université de Montpellier (Author)
  • Nataša Ravbar - , ZRC SAZU Karst Research Institute (Author)
  • Zhao Chen - , Chair of Groundwater Systems (Author)
  • Naomi Mazzilli - , Avignon Université (Author)
  • Hervé Jourde - , Université de Montpellier (Author)
  • Nico Goldscheider - , Karlsruhe Institute of Technology (Author)

Details

Original languageEnglish
Pages (from-to)2405–2430
Number of pages26
JournalHydrology and earth system sciences
Volume26
Issue number9
Publication statusPublished - 9 May 2022
Peer-reviewedYes

External IDs

Scopus 85130569712
Mendeley a7826314-0e30-3529-8233-c21a1c9e50d4
unpaywall 10.5194/hess-26-2405-2022

Keywords

ASJC Scopus subject areas