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What Can We Do to Forecast Tsunami Hazards in the Near Field Given Large Epistemic Uncertainty in Rapid Seismic Source Inversions?
Author(s) -
Cienfuegos Rodrigo,
Catalán Patricio A.,
Urrutia Alejandro,
Benavente Roberto,
Aránguiz Rafael,
González Gabriel
Publication year - 2018
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2018gl076998
Subject(s) - inversion (geology) , geology , categorical variable , seismic hazard , seismology , bayesian probability , warning system , hazard , uncertainty quantification , computer science , statistics , mathematics , telecommunications , chemistry , organic chemistry , tectonics
Abstract The variability in obtaining estimates of tsunami inundation and runup on a near‐real‐time tsunami hazard assessment setting is evaluated. To this end, 19 different source models of the Maule Earthquake were considered as if they represented the best available knowledge an early tsunami warning system could consider. Results show that large variability can be observed in both coseismic deformation and tsunami variables such as inundated area and maximum runup. This suggests that using single source model solutions might not be appropriate unless categorical thresholds are used. Nevertheless, the tsunami forecast obtained from aggregating all source models is in good agreement with observed quantities, suggesting that the development of seismic source inversion techniques in a Bayesian framework or generating stochastic finite fault models from a reference inversion solution could be a viable way of dealing with epistemic uncertainties in the framework of nearly‐real‐time tsunami hazard mapping.