R11—Surrogate-Based PTHA
Abstract
Abstract Surrogate model approaches – providing fast-running approximation of complex dynamical models – have been gaining traction in the geoscience community. They are highly efficient for uncertainty quantification, and, once trained for a given location, can be used without additional numerical resources and can be seen as a natural solution for PTHA in regions of the world where observations and modelling capacities are lacking. This recipe explores the application of surrogate modeling approaches to two different cases: (1) tsunami hazards in the northern Cascadia, and (2) meteotsunami hazards in the Adriatic Sea.
Fields of Study & Subjects
Earthquake and Tsunami Effects
Model Reduction and Neural Networks
Advanced Multi-Objective Optimization Algorithms
Publication details
- Journal / source
- Mathematics of planet earth
- Pages
- 475–483
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Book chapter