What is the most efficient sampling-based uncertainty propagation method in flood modelling?

Kesserwani, G. orcid.org/0000-0003-1125-8384, Hajihassanpour, M., Pettersson, P. et al. (1 more author) (2024) What is the most efficient sampling-based uncertainty propagation method in flood modelling? In: Gourbesville, P. and Caignaert, G., (eds.) Advances in Hydroinformatics—SimHydro 2023 Volume 1 New Modelling Paradigms for Water Issues. SimHydro 2023, 08-10 Nov 2023, Chatou, France. Springer Water, 1 . Springer Nature Singapore , pp. 367-386. ISBN 9789819740710

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Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Gourbesville, P.
  • Caignaert, G.
Copyright, Publisher and Additional Information:

© 2024 The Authors. Except as otherwise noted, this author-accepted version of a paper published in Advances in Hydroinformatics—SimHydro 2023 Volume 1 is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Earth Sciences; Physical Geography and Environmental Geoscience
Dates:
  • Published: 31 August 2024
  • Published (online): 30 August 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Mechanical, Aerospace and Civil Engineering
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/R007349/1
Depositing User: Symplectic Sheffield
Date Deposited: 14 Nov 2024 12:28
Last Modified: 14 Nov 2024 12:28
Status: Published
Publisher: Springer Nature Singapore
Series Name: Springer Water
Refereed: Yes
Identification Number: 10.1007/978-981-97-4072-7_24
Open Archives Initiative ID (OAI ID):

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