TY - JOUR
T1 - Toward Real-Time Ground-Shaking-Intensity Forecasting Using ETAS and GMM
T2 - Insights from the Analysis of the 2022 Taitung Earthquake Sequence
AU - Hsieh, Ming Che
AU - Chan, Chung Han
AU - Ma, Kuo Fong
AU - Yen, Yin Tung
AU - Chen, Chun Te
AU - Chen, Da Yi
AU - Liao, Yi Wun Mika
N1 - Publisher Copyright:
© Seismological Society of America.
PY - 2024/11
Y1 - 2024/11
N2 - Earthquake forecasting, combined with precise ground-shaking estimations, plays a pivotal role in safeguarding public safety, fortifying infrastructure, and bolstering the preparedness of emergency services. This study introduces a comprehensive workflow that integrates the epidemic-type aftershock sequence (ETAS) model with a preselected ground-motion model (GMM), facilitating accurate short-term forecasting of ground-shaking intensity (GSI), which is crucial for effective earthquake warning. First, an analysis was conducted on an earthquake catalog spanning from 1994 to 2022 to optimize the ETAS parameters. The dataset used in this analysis allowed for the further calculation of total, background, and clustering seismicity rates, which are crucial for understanding spatiotemporal earthquake occurrence. Subsequently, short-term earthquake activity simulations were performed using these up-to-date seismicity rates to generate synthetic catalogs. The ground-shaking impact on the target sites from each synthetic catalog was assessed by determining the maximum intensity using a selected GMM. This simulation process was repeated to enhance the reliability of the forecasts. Through this process, a probability distribution was created, serving as a robust forecasting for GSI at sites. The performance of the forecasting model was validated through an example of the Taitung earthquake sequence in September 2022, showing its effectiveness in forecasting earthquake activity and site-specific GSI. The proposed forecasting model can quickly deliver short-term seismic hazard curves and warning messages, facilitating timely decision making.
AB - Earthquake forecasting, combined with precise ground-shaking estimations, plays a pivotal role in safeguarding public safety, fortifying infrastructure, and bolstering the preparedness of emergency services. This study introduces a comprehensive workflow that integrates the epidemic-type aftershock sequence (ETAS) model with a preselected ground-motion model (GMM), facilitating accurate short-term forecasting of ground-shaking intensity (GSI), which is crucial for effective earthquake warning. First, an analysis was conducted on an earthquake catalog spanning from 1994 to 2022 to optimize the ETAS parameters. The dataset used in this analysis allowed for the further calculation of total, background, and clustering seismicity rates, which are crucial for understanding spatiotemporal earthquake occurrence. Subsequently, short-term earthquake activity simulations were performed using these up-to-date seismicity rates to generate synthetic catalogs. The ground-shaking impact on the target sites from each synthetic catalog was assessed by determining the maximum intensity using a selected GMM. This simulation process was repeated to enhance the reliability of the forecasts. Through this process, a probability distribution was created, serving as a robust forecasting for GSI at sites. The performance of the forecasting model was validated through an example of the Taitung earthquake sequence in September 2022, showing its effectiveness in forecasting earthquake activity and site-specific GSI. The proposed forecasting model can quickly deliver short-term seismic hazard curves and warning messages, facilitating timely decision making.
UR - http://www.scopus.com/inward/record.url?scp=85209078576&partnerID=8YFLogxK
U2 - 10.1785/0220240180
DO - 10.1785/0220240180
M3 - 期刊論文
AN - SCOPUS:85209078576
SN - 0895-0695
VL - 95
SP - 3264
EP - 3277
JO - Seismological Research Letters
JF - Seismological Research Letters
IS - 6
ER -