Advancing Earthquake Forecasting: Integrating Physics-Based and Statistical Approaches
A special issue of Geosciences (ISSN 2076-3263).
Deadline for manuscript submissions: 31 May 2025 | Viewed by 29
Special Issue Editors
Interests: statistical mechanics; statistical seismology; complex systems; stochastic modeling; disordered systems
Interests: statistical seismology; seismic hazard analysis; stochastic modeling; spatial statistics; tsunami hazard analysis
Interests: stochastic modeling; statistical seismology; seismic hazard analysis; earthquake forecasting; model testing
Special Issue Information
Dear Colleagues,
Spatio-temporal clustering of seismicity is one of the main features of the seismic process that allows us to build short-term earthquake forecasting models. Among different probabilistic models, the ETAS revolutionized statistical seismology by improving the forecasting of small-to-moderate earthquakes. However, its limitations in predicting large shocks and offering reliable mid- and long-term forecasts have led to the need for more advanced techniques. There is growing consensus that statistical approaches alone are insufficient for a significant improvement in seismic forecasting. Instead, a multilevel and interdisciplinary approach that integrates physics-based modeling is essential to enhance our forecasting capabilities, particularly for major events.
This Special Issue invites contributions on the latest research in physics-based stochastic modeling of natural and induced earthquakes, supported by multidisciplinary methods. We welcome studies on improving earthquake forecasting through stochastic models, geodesy, paleoseismic records, fluid dynamics, crustal stress analysis, and AI-driven models. Our emphasis is on bridging statistical and physics-based approaches to provide more reliable short- and long-term seismic hazard estimates.
Yours faithfully,
Dr. Petrillo Giuseppe
Dr. Matteo Taroni
Dr. Ilaria Spassiani
Dr. Simone Barani
Guest Editors
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Keywords
- stochastic modeling
- earthquake forecasting
- probabilistic forecasting
- time series analysis
- earthquake physics
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