Abstract
This study describes three earthquake occurrence models as applied to the whole Italian territory, to assess the occurrence probabilities of future (M ≥5.0) earthquakes: two as short-term (24 hour) models, and one as long-term (5 and 10 years). The first model for short-term forecasts is a purely stochastic epidemic type earthquake sequence (ETES) model. The second short-term model is an epidemic rate-state (ERS) forecast based on a model that is physically constrained by the application to the earthquake clustering of the Dieterich rate-state constitutive law. The third forecast is based on a long-term stress transfer (LTST) model that considers the perturbations of earthquake probability for interacting faults by static Coulomb stress changes. These models have been submitted to the Collaboratory for the Study of Earthquake Predictability (CSEP) for forecast testing for Italy (ETH-Zurich), and they were locked down to test their validity on real data in a future setting starting from August 1, 2009.
Highlights
Despite the notable lack of success for reliable prediction of destructive earthquakes, there has been a recent resurgence of research into earthquake predictability that is motivated by better monitoring networks and data of past events, new knowledge of the physics of earthquake ruptures, and a more comprehensive understanding of stress evolution and transfer
Unlike the old deterministic way of formulating earthquake predictions, which was based on various kinds of more or less popular precursors, much of the recent research into earthquake prediction is aimed at a quantitative specification of the uncertainty characterizing earthquake forecasts
We present here our 5-year and 10-year earthquake forecasts that are based on a long-term model that considers the perturbations of earthquake probability for interacting faults by static Coulomb stress changes, which we refer to as long-term stress transfer (LTST)
Summary
Despite the notable lack of success for reliable prediction of destructive earthquakes, there has been a recent resurgence of research into earthquake predictability that is motivated by better monitoring networks and data of past events, new knowledge of the physics of earthquake ruptures, and a more comprehensive understanding of stress evolution and transfer. Unlike the old deterministic way of formulating earthquake predictions, which was based on various kinds of more or less popular precursors, much of the recent research into earthquake prediction is aimed at a quantitative specification of the uncertainty characterizing earthquake forecasts. Stochastic short-term models that describe the phenomenon of earthquake clustering are achieving increasing success in the seismological community [e.g., Helmsetter et al 2006]. These models were proposed to answer the most common questions of the general public and the media that arise in particular after sizable events, such as, «What will happen next?» and, «What is the chance that another large earthquake will occur?»
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
