Articles | Volume 24, issue 4
https://doi.org/10.5194/nhess-24-1401-2024
https://doi.org/10.5194/nhess-24-1401-2024
Research article
 | 
24 Apr 2024
Research article |  | 24 Apr 2024

Scoring and ranking probabilistic seismic hazard models: an application based on macroseismic intensity data

Vera D'Amico, Francesco Visini, Andrea Rovida, Warner Marzocchi, and Carlo Meletti

Viewed

Total article views: 592 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
451 107 34 592 40 25 28
  • HTML: 451
  • PDF: 107
  • XML: 34
  • Total: 592
  • Supplement: 40
  • BibTeX: 25
  • EndNote: 28
Views and downloads (calculated since 24 Nov 2023)
Cumulative views and downloads (calculated since 24 Nov 2023)

Viewed (geographical distribution)

Total article views: 592 (including HTML, PDF, and XML) Thereof 575 with geography defined and 17 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 May 2024
Download
Short summary
We propose a scoring strategy to rank multiple models/branches of a probabilistic seismic hazard analysis (PSHA) model that could be useful to consider specific requests from stakeholders responsible for seismic risk reduction actions. In fact, applications of PSHA often require sampling a few hazard curves from the model. The procedure is introduced through an application aimed to score and rank the branches of a recent Italian PSHA model according to their fit with macroseismic intensity data.
Altmetrics
Final-revised paper
Preprint