Reproducing the Spatial Characteristics of High-Frequency Ground Motions for the 1850 M 7.5 Xichang Earthquake

Reproducing the spatial characteristics of large historical earthquakes and predicting the strong ground motions of future destructive large earthquakes through actual small earthquakes have high-practical value. The empirical Green’s function method is a numerical simulation method that can impart real seismic information in synthetic ground motions. In this article, we use data from the 2018 M 5.1 Xichang earthquake to reproduce the ground-motion characteristics of the 1850 M 7.5 Xichang earthquake using the empirical Green’s function method. The uncertainties of the parameters, such as the number, area, and locations of asperities, are considered. The synthetic time histories, peak ground accelerations (PGAs), and response spectra are obtained through simulation. The main results are as follows. (1) The synthetic Xichang earthquake (such as the ground-motion intensity and attenuation characteristic of the PGA) matches well with the M 8.0 Wenchuan earthquake and M 7.3 Jiji earthquake. When the number of asperities is 1 or 2, the PGA characteristics of the Xichang earthquake match well not only with the Next Generation Attenuation-West2 (2014) ground-motion model in the range of 100 km but also with the seismic ground-motion parameter zonation map of China in the range of 20–100 km. (2) The prediction results based on the asperity source model are relatively reliable in the range of 20–100 km. The one-asperity and two-asperity models of the Xichang earthquake match better than the three-asperity and four-asperity models. (3) We can speculate that when the M 7.5 earthquake struck the Xichang area, the damage was relatively strong. The PGA may have exceeded 1.0g in the meizoseismal area, and the seismic intensity in the meizoseismal area may have reached or exceeded a degree of X–XI. Therefore, the synthesized M 7.5 Xichang earthquake has the strength characteristics of a large destructive earthquake.

Intensity of Induced Earthquakes in Northeast British Columbia, Canada

The damage potential of induced earthquakes associated with fluid injection is a major concern in hydrocarbon resource development. An important source of data for the assessment of damage is macroseismic intensity perceived by people and structures. In the Western Canada Sedimentary Basin (WCSB) where the occurrence of seismicity is mostly related to oil and gas activities, the collection of intensity data is incomplete. In this study, we present a comprehensive dataset gathered by the BC Oil and Gas Commission in the period 2016–2020. We assign intensities to individual felt reports according to the modified Mercalli intensity (MMI) scale and associate each MMI value to an earthquake. The isoseismal map of the largest earthquake in the Septimus region of northeast British Columbia is also provided using the compiled intensity dataset complemented with data from the U.S. Geological Survey and Natural Resources Canada “Did You Feel It?” systems along with the intensities converted from ground-motion amplitudes. We consider an approximate 10 km radius around the mainshock of 30 November 2018 earthquake with moment magnitude of 4.6 to be the meizoseismal area based on maximum intensities of 4–5. We also investigate the distance decay of intensity for shallow induced earthquakes in comparison with deeper natural events with the same magnitudes. Although intensities from shallow earthquakes (depth≤5 km) can be higher than deep events (depth≥10 km) at close distances (10–15 km), they tend to decrease abruptly at greater distances to become lower than deep events. The localization of large intensities from induced earthquakes within the meizoseismal area warrants special attention in future resource developments and call for systematic intensity data collection in the WCSB.

Application of fiber-reinforced concrete lining for fault-crossing tunnels in meizoseismal area to improving seismic performance

The fault-crossing tunnel in meizoseismal area is directly subjected to strong ground motion, which leads to the failure of the tunnel lining. In order to improve the seismic safety of tunnel, fiber-reinforced concrete is applied to tunnel lining in this article. Taking the section of Zhongyi tunnel crossing Wanlong fault as an example, seismic performance of fiber-reinforced concrete tunnel lining was studied by finite difference numerical calculation software FLAC3D. The seismic displacement, stress response, and side wall convergence of secondary lining structures which are plain concrete, steel fiber-reinforced concrete, and steel-basalt hybrid fiber-reinforced concrete were comparatively analyzed. Moreover, the safety factor of each lining structure was investigated with the present numerical model. With the obtained data, seismic performance of steel-basalt hybrid fiber-reinforced concrete secondary lining is better than that of steel fiber-reinforced concrete secondary lining. The results may provide references for seismic design of fault-crossing tunnels in meizoseismal area.

Research on the Application of Phone Location Data in the Rapid Delimitation of the Meizoseismal Area

After an earthquake, rapidly assessing the affected areas, particularly the meizoseismal area, is crucial to emergency rescue work. Currently, many methods exist for delimiting the range of the area affected by an earthquake. The main method for estimating this area is to use an empirical model of the seismic intensity attenuation relationship. In contrast, this article uses the change rate (CR) of the phones’ location data in an area after the earthquake to infer the extent of the meizoseismal area. This study selects phone location data from eight earthquakes for experimentation and analysis. The results show a correlation between the phone location data and the actual distribution of the meizoseismal area based on intensity maps that were issued by the China Earthquake Administration. According to the results, the extent of the meizoseismal area can be estimated by the magnitude, the focal depth, the CR, the time of the earthquake, and the distance to the epicenter. The magnitude, CR, and focal depth are dominant and are positively correlated with the intensity. Based on the aforementioned parameters, a calculation model for delimiting the extent of the meizoseismal area based on phone location data can be constructed. The accuracy of the correlation coefficient of fitting result is 0.7826, and the R2 value is 0.6125. The results demonstrate that phone location data can be used to quickly delimit the meizoseismal area and can provide a basis for earthquake emergency rescue work.

Failure modes of loose landslide deposits in 2008 Wenchuan earthquake area in China

In this study, a geological investigation and statistical analysis of the post-earthquake slope deposit failures in a meizoseismal area were presented, with a selected example from the 2008 Ms 8.0 Wenchuan earthquake occurred in Sichuan Province in China. The typical slope deposit failures were surveyed in three meizoseismal areas, namely Qingchuan county in Guangyuan city, Beichuan county in Mianyang city, and the epicenter area, Wenchuan county in Aba Tibetan Autonomous Prefecture. According to the movement, material and deformation mechanism of rock or soil, the failures of the post-earthquake landslide deposit could be subdivided into four categories, i.e. slide, collapse, erosion and flow. This classification of failures of landslide deposit considers the topographic and failure after the earthquake. Besides, some other important factors such as topography, lithology and hydrogeology are also considered. The above mentioned four failure categories are further split into 12 sub-classification. The complicated deformation mechanism and different failure patterns of the slope deposits are analyzed in typical deposits. This classification provides a good reference for the prediction of geological hazards, whereas mitigation of the landslide or debris flows caused by loose deposits in the meizoseismal area is still a difficult task.