Examining the spatial and temporal distribution of seismic activity holds significant importance for seismic risk assessment, particularly in regions prone to frequent and intense earthquakes such as the Sichuan-Yunnan region in China. It is widely recognized that earthquakes exhibit non-random patterns in both spatial and temporal dimensions.
Early scientists endeavored to predict earthquakes using statistical principles, leading to the development of various forecasting methods. Among these, the Relative Intensity(RI)and Pattern Informatics(PI)methods emerged as statistical approaches to earthquake prediction modeling. Essentially, both methods fall under the category of smoothing seismic activity models. They employ techniques to quantify temporal changes in seismic activity graphs, generating maps that highlight areas(hot spots)where earthquakes may occur during specific future periods. While the RI algorithm’s theory is straightforward, its forecasting efficacy is robust, particularly notable in predicting major earthquakes, demonstrating similar advantages to the PI algorithm. Widely adopted globally for proactive predictions across diverse tectonic systems, it has shown commendable results in seismic forecasting practices both domestically and internationally. Over years of development, its predictive performance has gained prominence. However, further research is needed to assess its suitability for predicting minor seismic events in low-seismicity zones. Additionally, its successful application hinges on background seismic activity and the selection of target magnitudes.
To aid seismic activity prediction in the Sichuan-Yunnan region and identify potential future seismic source areas, a comprehensive parameter analysis was conducted using the Relative Intensity(RI)algorithm with the parameter traversal test(PTT). The RI algorithm operates on the premise that the predicted intensity of future earthquakes in a given region closely mirrors the intensity of past earthquakes. While it may not explicitly consider the “active” and “quiet” characteristics of seismic activity, as a fundamental prediction algorithm, it often yields improved prediction outcomes when applied to assess seismic probability in regions with high seismic activity, such as the Sichuan-Yunnan region.
In this study, the statistical-based Relative Intensity(RI)algorithm is employed to calculate the relative intensity of earthquakes based on quantitative earthquake characteristics. The study involves gridding the investigated area and statistically analyzing historical earthquake occurrences within each grid unit under specific magnitude conditions to inform predictions of future earthquake frequencies. The research focuses on evaluating the influence of four key model parameters: grid size, length of the anomalous learning window, starting point of the prediction window, and length of the prediction window, on the algorithm’s prediction efficiency. Furthermore, the study investigates the applicability of the RI algorithm to the Sichuan-Yunnan regions in China. The results yield two significant findings:
(1)The integration of the Relative Intensity(RI)algorithm with the Parameter Traversal Test(PTT)yielded significantly improved results compared to random guessing, primarily due to its optimized parameter selections. These parameters include the grid size, length of the anomalous learning time window, starting time of the prediction time window, and length of the prediction time window.
(2)The parameters of the prediction model exhibit a degree of stability and demonstrate predictive capability for seismic activity in the Sichuan-Yunnan region over the next 1-5 years. The study revealed specific rules and effective parameter intervals applicable to earthquake-prone areas in Sichuan-Yunnan.
The findings suggest that the integration of the Relative Intensity(RI)algorithm with the Parameter Traversal Test(PTT)holds promise for predicting seismic activities in the Sichuan-Yunnan region. This approach enhances the pool of references available for predicting earthquake trends in regions prone to frequent and intense earthquakes. Further research on the RI algorithm is anticipated to yield a more refined numerical model for earthquake trend prediction, contributing to enhanced forecasting accuracy and preparedness in earthquake-prone areas.
The Longmenshan fault zone is located in the northeastern margin of the Qinghai-Tibet plateau, with an overall direction of NNE and a total length of about 500km. As we have known, the Longmenshan fault zone is the boundary fault between the Bayanqala block and Sichuan basin. Since the Cenozoic, the Longmenshan fault zone has experienced intense tectonic activity and multi-stage magmatic activity, forming a series of active faults with different scales and properties.
And Lushan MS7.0 earthquake in 2013 and Lushan MS6.1 earthquake in 2022 occurred in the southern section of Longmenshan fault zone, and the two earthquakes were only 10km far away apart. The generation of the two strong earthquakes is closely related to the seismic tectonic environment and crustal physical structure parameters. So to study the characteristics of shallow crustal physical structure and its relationship with deep dynamic processes, is good for us to understand the seismogenic environment of this area. The wide angle inverse/refraction detection method is an effective means to obtain the physical property parameters of the crust. In this paper we extracted the first arrival travel time data of P-wave and S-wave from Jinchuan-Lushan-Leshan deep seismic sounding(DSS)profile data. The 2D ray-tracing travel-time imaging method proposed by Zelt et al.(1998)was used to obtain the 2D P-wave, S-wave and Poisson’s ratio structure of the upper crust in the source area of the Lushan strong earthquake and its adjacent area. Then based on the results of deep crust exploration, seismic distribution characteristics and other geophysical and geological studies in this area, we focus on the response of shallow tectonic environment and deep dynamic processes in the upper crust, and analyze the seismogenic environment and seismogenic mechanism of M6-7 strong earthquakes in this area. The results show that: 1)The crustal velocity and Poisson’s ratio are significantly different at different positions of the profile. In the Songpan-Ganzi block, the velocities of P- and S-waves in the upper crust are relatively high and the Poisson’s ratio is relatively low. While in the Sichuan basin, the velocities of P- and S-waves in the upper crust are relatively low and the Poisson’s ratio is relatively high. In Longmenshan tectonic belt which between the Songpan-Garze block and the Sichuan basin, the velocities of P- and S-waves and Poisson’s ratio isolines of the upper crust are controlled by regional tectonic activities, which are basically consistent with the occurrence of the strata and show a near-vertical trend. The sedimentary basement below the tectonic transition zone shows obvious structural differences, and the velocity and Poisson’s ratio contour lines form “V” shape characteristics. 2)The characteristics of high crust velocity and low Poisson ratio(<0.26) in the Songpan-Ganzi block may be the direct reflection of the strong deformation of Sinian-Paleozoic strata caused by the orogenic activities in the northeastern margin of the Qinghai-Tibet plateau in the Indosinian period, and the bi-direction contraction of the strata in the Triassic Xikang Group, the obvious thickening of the crust, and the multi-stage magmatic activities. 3)The large lateral variation gradient of velocity and Poisson’s ratio in Longmenshan tectonic belt between Songpan-Ganzi block and Sichuan basin is the direct evidence of vertical crustal deformation caused by the compression of low Poisson’s ratio crust from the eastern margin of Qinghai-Tibet plateau to the hard Yangzi platform(high Poisson’s ratio)by the remote effect of the collision between the Indian plate and the Asian plate since late Quaternary. 4)The aftershocks of the MS7.0 earthquake mainly occurred on the high-velocity and Low-Poisson’s ratio side of the velocity and Poisson’s ratio gradient belts in the crust. The seismicity in this area is not only controlled by the regional fault structure, but also closely related to the physical structure characteristics of the upper crust.
The Red River Fault in western Yunnan is one of the longest strike-slip faults in China and has a high seismic potential. To investigate its complicated structure, a near-NS directed 300km long wide-angle reflection/refraction seismic profile was laid out from Yunxian to Ninglang, across the Red River Fault. The 2-D velocity structure model along the profile was obtained through 1-D and 2-D analysis and fitting the observed data with combination of first-arrival traveltime tomography and forward modeling. The results indicate:In the crust, the average P-wave velocity is 6.2~6.3km/s and basically shows a positive gradient structure, but there are some low velocity anomalies at different area in upper and lower crust. Regarding the crust boundary, a relative large lateral variation exists in the depth of Moho, which goes deeper from south to north, ranging from 45km to as deep as 54km; compared to other typical continental crust, the study area demonstrates a striking thickening. It should be mentioned that the crustal thickening is mainly observed in the lower crust, while the upper and middle crust possess nearly constant thickness. We observed strong seismic velocity contrast across the Red River Fault, which emphasizes the role of the fault as an important tectonic boundary between Yangtze paraplatform and Sanjiang geosynclinal system. Along the profile, the Moho depth has no remarkable variation when crossing the Red River Fault. Combining with other study results on nearby area, it proves that there is notable heterogeneity between different parts of the Red River Fault.
DSS data of Bohai Bay profile was processed in August 2011 and the result obtained in this paper and the results of other profiles,which cross this profile,were interpreted comprehensively in this paper. The DSS data were calculated and interpreted synthetically using 1-D and 2-D processing techniques in order to find out the basic features of 2-D velocity structures,spatial distribution of faults,geological structure of shallow and deep crust in the southwest margin of Bohai Bay and adjacent areas. The result shows that obvious layered structure appears along the profile,and the crustal velocity structures in different regions have obvious heterogeneity in the lateral and vertical directions. The crystalline basement near the Bohai Bay is gradually thinning southwestwards,and beneath the 220km Stake,the depth of G interface is 7.4km. The thickness of the middle layer varies greatly,with the change range up to 4.0km. The crustal depth varies relatively moderately,with a change range of about 2.0km. The Moho deepens gradually from coastal area to the inland along the southwest direction.