Group C, Poster #197, Earthquake Forecasting and Predictability (EFP)

Prediction and validation of short- to long-term earthquake probabilities in inland Japan using the hierarchical space-time ETAS and space-time Poisson process models

Yosihiko Ogata
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2022 SCEC Annual Meeting, Poster #197, SCEC Contribution #12003 VIEW PDF
A hierarchical space-time version of the epidemic-type aftershock sequence (HIST-ETAS) model was constructed for an optimally adapted fit to diverse seismicity features characterized by anisotropic clustering as well as regionally distinct parameters. This manuscript validates this elaborate model for short-term prediction based on several years of recent inland Japan earthquakes as a testing dataset, by evaluating the results using a log-likelihood ratio score. To consider intermediate- and long-term performance, several types of space-time Poisson models are compared with the background seismicity rate of the HIST-ETAS model. Results show firstly that the HIST-ETAS model has the best short...-term prediction results for earthquakes in the range of magnitudes from M4.0 to M5.0, although, for the larger earthquakes, sufficient recent earthquake data is lacking to evaluate the performance. Second, for intermediate-term predictions, the optimal spatial nonuniform Poisson intensity model has a better forecast performance than the seismic background intensity of the HIST-ETAS model, while the uniform rate Poisson model throughout all of inland Japan has the worst forecast performance. For earthquakes of M6 or larger, the performance of retrospective long-term forecasts was tested in two ways. First, a retrospective forecasting experiment divided the entire period from 1885 to the present into two parts, with the recent ~30 years as the forecast period. Second, the historical damaging earthquake data (1500 –1884) were spatially validated using century data from 1885 to the present. In both validations, it was determined that the spatial intensity of the inland background seismic activity of the HIST-ETAS model is much better than the best-fit nonuniform Poisson spatial model, leading to the best results. The findings of this study will be critical for regional earthquake hazard planning in Japan and similar locations worldwide.
Reference
Ogata, Y. (2022). Prediction and validation of short-to-long-term earthquake probabilities in inland Japan using the hierarchical space–time ETAS and space–time Poisson process models, Earth Planets Space, 74, 110, https://doi.org/10.1186/s40623-022-01669-4.
Ogata Y, et al. (2021) Hierarchical space-time point-process models (HIST-PPM): Software documentation and codes, Computer Science Monographs, The Institute of Statistical Mathematics, 35. doi: https://www.ism.ac.jp/editsec/csm/pdf/csm_035.pdf.
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Citation: Ogata, Y. (2022, 09). Prediction and validation of short- to long-term earthquake probabilities in inland Japan using the hierarchical space-time ETAS and space-time Poisson process models. Poster Presentation at 2022 SCEC Annual Meeting.
Keywords: Bayesian method, cross-validation, HIST-ETAS, location-dependent parameters, maximum a posteriori (MAP), space-time log-likelihood score, spatial log-likelihood score, plug-in predictor
Relevant SCEC Themes:
Data-Intensive Computing
Probabilistic Seismic Hazard Analysis
Operational Earthquake Forecasting