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Tsunami inundation from heterogeneous earthquake slip distributions: Evaluation of synthetic source models
Author(s) -
Davies Gareth,
Horspool Nick,
Miller Victoria
Publication year - 2015
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1002/2015jb012272
Subject(s) - geology , slip (aerodynamics) , seismology , subduction , moment magnitude scale , seismic hazard , tectonics , geometry , physics , mathematics , scaling , thermodynamics
This study investigates whether eight different synthetic finite fault models (SFFM) can simulate stochastic earthquake‐tsunami with similar statistical properties to “real” earthquake‐tsunami events, where the latter are represented using heterogeneous slip distributions from 66 Finite Fault Inversions (FFI) for oceanic subduction interface earthquakes. A new method is derived to estimate SFFM parameters from FFI, and predictive relations between the earthquake moment magnitude and the SFFM corner wave numbers are developed to support model applications. SFFM with more capacity to spatially localize slip are better able to simulate higher slip regions on the FFI, and this strongly influences their associated tsunami inundation, which is computed in two dimensions over idealized topography. The best performing SFFM generates tsunami inundation which envelopes the FFI inundation in 81% of cases using 10 synthetic events (close to the ideal value of 82%), while the other SFFM show greater tendencies to underestimate inundation. These differences are related to the capacity of each SFFM to produce spatially localized slip distributions. None of the SFFM showed a tendency to overpredict inundation. The results highlight that SFFM cannot be assumed to reliably quantify uncertainties in the tsunami inundation of real earthquakes, and the use of untested SFFM could create nonconservative bias in tsunami hazard assessments. However, the most successful model used here performs quite well, although it may still underestimate inundation more often than an optimal model.