SCEC Award Number 19089 View PDF
Proposal Category Individual Proposal (Data Gathering and Products)
Proposal Title Earthquake Simulators, Statistics and Software: Forecasting, Nowcasting, and Tsunami Early Warning-II
Investigator(s)
Name Organization
John Rundle University of California, Davis
Other Participants Graduate Student Researcher - 1
SCEC Priorities 5a, 5b, 5c SCEC Groups CS, EFP, SDOT
Report Due Date 04/30/2020 Date Report Submitted 05/11/2020
Project Abstract
 We continued our research on the themes that have been our focus for the previous 2 years, adding new capabilities to our Virtual Quake and Tsunami Squares technologies to make them useful for third party users. We developed new scientific techniques for earthquake and tsunami analysis, nowcasting using statistical communication theory, forecasting, and early warning that grow out of recent work presented at the SCEC 2019 annual meeting. We further applied new ideas for invasion percolation to the problem of induced earthquakes. Additionally, began to apply machine learning methods via convolutional neural networks, random forests, and hidden Markov models to synthetic and real earthquake data, to determine whether space-time patterns of earthquakes seen in simulations can be detected in observed data
Intellectual Merit Contributed to a fundamental new understanding of earthquakes and tsunami dynamics and foreasting.
Broader Impacts New methods were developed to address the problem of earthquake forecasting.
Exemplary Figure Refer to the figure in the project report, a montage of a tsunami propagating across the Pacific basin from the Tohoku source region.