17:15 〜 19:15
[SGD03-P13] Source parameters and rapid simulation of the strong ground motion of the Ms 6.8 earthquake on January 7, 2025, in Dingri, Xizang, China, derived from InSAR observation
キーワード：InSAR, Lutan-1 SAR , Dingri earthquake, Source parameters, strong ground motion
On January 7, 2025, an Ms 6.8 earthquake struck Dingri County, Xizang in China, with an epicenter of 87.45 ° E, 28.50 ° N, and a depth of about 10 km, resulting in numerous casualties. This earthquake occurred near the Dengmo Fault within the Lhasa block of the Qinghai-Tibet Plateau, an area with significant extensional tectonic movement and seismic activity under the collision of the Indian Plate and the Eurasian Plate. Synthetic Aperture Radar Interferometry (InSAR) deformation monitoring is an efficient way to quickly acquire coseismic deformation and fault slip distribution after earthquakes. The inversion of the earthquake source mechanism helps determine the geometric characteristics of the seismogenic fault, understand the structural activity characteristics and seismogenic mechanism, and simulate strong ground motion, which is beneficial for guiding emergency response at earthquake sites.
This study utilized the ascending data (2024-12-06 and 2025-01-07) of Lutan-1 (LT-1), China’s first civilian L-band SAR satellite constellation, and the descending data from Sentinel-1 Track48 (2024-12-27 and 2025-01-08) to extract the coseismic deformation field of Dingri Earthquake for the focal mechanism inversion. The LT-1 coseismic deformation field showed that the maximum line-of-sight (LOS) deformation is about -2 m, and Sentinel-1 Track48 data indicated a maximum LOS deformation of 0.8 m, both suggesting that the earthquake was a normal fault rupture process with vertical and east-west extensional deformation and stemmed from the Dengme Co fault. Then, a two-step fault parameter inversion algorithm under constraints of InSAR results was applied to invert the seismogenic fault’s geometric parameters and slip distribution. The random search particle swarm optimization (PSO) algorithm was employed to determine the spatial geometry of the fault, including the location, depth, strike, and dip angle, and the distributed fault model was further used to calculate the slip distribution along the fault. Dip angles of 35°–55° were used and the optimal smoothing coefficient is 4.0. The distributed fault model simulation shows that the earthquake occurred along a normal fault with a strike of 187° and a dip angle of 40°, with a maximum fault displacement of 6 m. The moment magnitude reached Mw 7.1, and the coseismic slip propagated to the surface, consistent with the surface rupture observed in field investigations.
To quickly assess the distribution and characteristics of seismic ground motion, the seismic intensity distribution of the Dingri Earthquake was estimated by a random vibration finite fault model accounting for the fault rupture parameters derived from InSAR results and the shallow velocity structures at the site. The forward modeling results indicate that the maximum seismic intensity of the Dingri Earthquake could reach IX, primarily distributing at Dingri County. The spatial distribution and intensity range of the seismic effects closely align with the results published by the China Earthquake Administration. The optical image interpretation of surface rupture zones also confirmed that the location of the surface rupture zones north of Nixia Co Lake is consistent with the severely earthquake-stricken area acquired by the InSAR coseismic deformation field, with a maximum LOS coseismic displacement of nearly 1.5 m which is in agreement with field data. The seismic intensity results suggest that the region experienced significant destructive effects, with an intensity of IX.
Integrating InSAR-derived coseismic deformation fields and the two-step fault parameter inversion algorithm to acquire the source mechanism and rupture parameters of the earthquake enables quick identification of the severely earthquake-stricken area. It provides accurate data support for earthquake emergency response, intensity estimation, and hazard analysis. However, the high unpredictability of seismic disasters and delayed availability of SAR images make timely acquisition of coseismic deformation challenging. The short revisit cycle (4 days) of the LT-1 SAR satellite constellation proved particularly advantageous in supporting emergency rescue for earthquakes. Additionally, LT-1 can effectively avoid the decoherence effect caused by excessive surface rupture and obtain more effective co-seismic deformation signals of earthquakes. In the future, leveraging the advantages of new-generation SAR satellites in the accessibility, timeliness, and integrity of data acquisition and coverage can significantly improve support for earthquake emergency response and scientific research.
This study utilized the ascending data (2024-12-06 and 2025-01-07) of Lutan-1 (LT-1), China’s first civilian L-band SAR satellite constellation, and the descending data from Sentinel-1 Track48 (2024-12-27 and 2025-01-08) to extract the coseismic deformation field of Dingri Earthquake for the focal mechanism inversion. The LT-1 coseismic deformation field showed that the maximum line-of-sight (LOS) deformation is about -2 m, and Sentinel-1 Track48 data indicated a maximum LOS deformation of 0.8 m, both suggesting that the earthquake was a normal fault rupture process with vertical and east-west extensional deformation and stemmed from the Dengme Co fault. Then, a two-step fault parameter inversion algorithm under constraints of InSAR results was applied to invert the seismogenic fault’s geometric parameters and slip distribution. The random search particle swarm optimization (PSO) algorithm was employed to determine the spatial geometry of the fault, including the location, depth, strike, and dip angle, and the distributed fault model was further used to calculate the slip distribution along the fault. Dip angles of 35°–55° were used and the optimal smoothing coefficient is 4.0. The distributed fault model simulation shows that the earthquake occurred along a normal fault with a strike of 187° and a dip angle of 40°, with a maximum fault displacement of 6 m. The moment magnitude reached Mw 7.1, and the coseismic slip propagated to the surface, consistent with the surface rupture observed in field investigations.
To quickly assess the distribution and characteristics of seismic ground motion, the seismic intensity distribution of the Dingri Earthquake was estimated by a random vibration finite fault model accounting for the fault rupture parameters derived from InSAR results and the shallow velocity structures at the site. The forward modeling results indicate that the maximum seismic intensity of the Dingri Earthquake could reach IX, primarily distributing at Dingri County. The spatial distribution and intensity range of the seismic effects closely align with the results published by the China Earthquake Administration. The optical image interpretation of surface rupture zones also confirmed that the location of the surface rupture zones north of Nixia Co Lake is consistent with the severely earthquake-stricken area acquired by the InSAR coseismic deformation field, with a maximum LOS coseismic displacement of nearly 1.5 m which is in agreement with field data. The seismic intensity results suggest that the region experienced significant destructive effects, with an intensity of IX.
Integrating InSAR-derived coseismic deformation fields and the two-step fault parameter inversion algorithm to acquire the source mechanism and rupture parameters of the earthquake enables quick identification of the severely earthquake-stricken area. It provides accurate data support for earthquake emergency response, intensity estimation, and hazard analysis. However, the high unpredictability of seismic disasters and delayed availability of SAR images make timely acquisition of coseismic deformation challenging. The short revisit cycle (4 days) of the LT-1 SAR satellite constellation proved particularly advantageous in supporting emergency rescue for earthquakes. Additionally, LT-1 can effectively avoid the decoherence effect caused by excessive surface rupture and obtain more effective co-seismic deformation signals of earthquakes. In the future, leveraging the advantages of new-generation SAR satellites in the accessibility, timeliness, and integrity of data acquisition and coverage can significantly improve support for earthquake emergency response and scientific research.