Summary
A moment magnitude (Mw) 5.0 earthquake hit Qiaojia, Yunnan, China on May 18, 2020. Its hypocenter is only approximately 20 km away from the Baihetan reservoir, the second largest hydropower station in China. The Baihetan Reservoir is located at the junction of multiple fault zones on the eastern boundary of the Sichuan-Yunnan rhombic block, an area with high background seismic activity. The Baihetan Reservoir was planned to be impounded in April 2021 and the MW 5.0 earthquake occurred during its water-retaining. Thus, it is critical to investigate the seismogenesis of the Qiaojia MW 5.0 mainshock and evaluate the risk of inducing earthquakes near the Baihetan Reservoir after impoundment. In this study, we built a complete and accurate earthquake catalog to analyze seismicity in the reservoir area before and after the MW 5.0 Qiaojia earthquake. We adopted a machine learning-based seismic phase picker, PhaseNet, to automatically detect seismic picks from continuous raw seismic data. Seismic phase picks were associated and located using sequential earthquake association and location methods, including REAL, VELEST and hypoDD. We eventually obtained high-precision locations of 1640 earthquakes by the hypoDD. The distribution of earthquake locations indicates that a concealed fault nearly vertical to the surface accommodated the MW 5.0 Qiaojia mainshock. The majority of its aftershocks is located within a narrow depth range of 8–13 km, indicating that the stresses in the hypocentral area were concentrated near the hypocenter of the MW5.0 earthquake. Along with focal mechanism solutions, we suggested that the Mw 5.0 Qiaojia earthquake is more likely a tectonic earthquake. However, we cannot exclude the possibility that earthquakes could be induced after the impoundment of Baihetan Reservoir, because the identified concealed fault is located in the middle of many large fault zones and only 20 km away from the Baihetan Reservoir.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.