Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 22, issue 8
Articles | Volume 22, issue 8
https://doi.org/10.5194/nhess-22-2491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-2491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 8
Research article
 | 
03 Aug 2022
Research article |  | 03 Aug 2022

Multilevel multifidelity Monte Carlo methods for assessing uncertainty in coastal flooding

Mariana C. A. Clare, Tim W. B. Leijnse, Robert T. McCall, Ferdinand L. M. Diermanse, Colin J. Cotter, and Matthew D. Piggott

Viewed

Total article views: 1,611 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,136 424 51 1,611 37 32
  • HTML: 1,136
  • PDF: 424
  • XML: 51
  • Total: 1,611
  • BibTeX: 37
  • EndNote: 32
Views and downloads (calculated since 24 Mar 2022)
Cumulative views and downloads (calculated since 24 Mar 2022)

Viewed (geographical distribution)

Total article views: 1,611 (including HTML, PDF, and XML) Thereof 1,515 with geography defined and 96 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 Apr 2024
Download
Short summary
Assessing uncertainty is computationally expensive because it requires multiple runs of expensive models. We take the novel approach of assessing uncertainty from coastal flooding using a multilevel multifidelity (MLMF) method which combines the efficiency of less accurate models with the accuracy of more expensive models at different resolutions. This significantly reduces the computational cost but maintains accuracy, making previously unfeasible real-world studies possible.
Read more
Altmetrics
Final-revised paper
Preprint