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Establishment of a seismic topographic effect prediction model in the Lushan Ms 7.0 earthquake area

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SUMMARYThe seismic topographic effect is one of the debated research topics in seismology and earthquake engineering. This debate is due to the discrepancy between the observed amplification and the amplification underestimation in numerical simulations. Although the numerical simulation of ground motion, which began in the 1970s, has been an important and effective way to study topographic effects, the quantitative mathematical model of topographic amplification is urgent. The actual influences on ground motion due to the topography depends on multiple topographic features, such as the topographic slope, topographic geometrical scale. To date, no definite conclusions regarding the main influencing factors and how to express the influencing factors have been made. In this paper, by introducing the back-propagation (BP) neural network technique, a set of mathematical parameters are determined to establish a quantitative topographic effect prediction model. These parameters are the elevation, the first gradient of the elevation and the higher order gradient in two orthogonal directions. Theoretically, the set of mathematical parameters is directly related to the simple topographic features, such as the elevation, topographic slope and height-to-width ratio. Furthermore, their combinations indirectly denote the complex topographic geometrical features, such as the different topographic geometrical scales, designated by the elevation (large-scale variable), the first gradient (middle-scale variable), the second-order gradient (small-scale variable) and so on (smaller scale variable), and the hill ridges that correspond to the sites with the first gradient of the elevation equal to zero and an elevation larger than its surrounding. In 2013, an earthquake of Ms 7.0 occurred in the Lushan area of Sichuan Province in Western China, where the topography sharply fluctuates. At station 51BXD, an acceleration was recorded close to 1.0 g, while at station 51BXM (14 km away from station 51BXD), the acceleration was recorded at only 0.2–0.3 g. In this paper, the spectral element method (SEM) is used to simulate the ground motion in the Lushan Ms 7.0 earthquake area. Then, the topographic amplification ratio of the simulated ground motion is calculated. Furthermore, a BP topographic amplification prediction model is established and compared based on different parameters. A rms of less than or close to 10 per cent between the BP model prediction results and topographic amplification ratio calculated using the simulated ground motion suggests that the parameters of the topographic elevation, the first gradient of the elevation and the second-order gradient in two orthogonal directions are enough to provide the acceptable topographic effect model in the Lushan area. Finally, using the prediction model, the topographic spectral ratio at stations 51BXD and 51BXM is predicted, and the topography amplification due to the scattering of seismic waves by the irregular topography at 51BXD is found to be 1.5–2 times that of 51BXM. The most important highlights of this paper identify the main factors of the topographic effect for the first time and provide an effective method for establishing a quantitative topographic effect prediction model.
Title: Establishment of a seismic topographic effect prediction model in the Lushan Ms 7.0 earthquake area
Description:
SUMMARYThe seismic topographic effect is one of the debated research topics in seismology and earthquake engineering.
This debate is due to the discrepancy between the observed amplification and the amplification underestimation in numerical simulations.
Although the numerical simulation of ground motion, which began in the 1970s, has been an important and effective way to study topographic effects, the quantitative mathematical model of topographic amplification is urgent.
The actual influences on ground motion due to the topography depends on multiple topographic features, such as the topographic slope, topographic geometrical scale.
To date, no definite conclusions regarding the main influencing factors and how to express the influencing factors have been made.
In this paper, by introducing the back-propagation (BP) neural network technique, a set of mathematical parameters are determined to establish a quantitative topographic effect prediction model.
These parameters are the elevation, the first gradient of the elevation and the higher order gradient in two orthogonal directions.
Theoretically, the set of mathematical parameters is directly related to the simple topographic features, such as the elevation, topographic slope and height-to-width ratio.
Furthermore, their combinations indirectly denote the complex topographic geometrical features, such as the different topographic geometrical scales, designated by the elevation (large-scale variable), the first gradient (middle-scale variable), the second-order gradient (small-scale variable) and so on (smaller scale variable), and the hill ridges that correspond to the sites with the first gradient of the elevation equal to zero and an elevation larger than its surrounding.
In 2013, an earthquake of Ms 7.
0 occurred in the Lushan area of Sichuan Province in Western China, where the topography sharply fluctuates.
At station 51BXD, an acceleration was recorded close to 1.
0 g, while at station 51BXM (14 km away from station 51BXD), the acceleration was recorded at only 0.
2–0.
3 g.
In this paper, the spectral element method (SEM) is used to simulate the ground motion in the Lushan Ms 7.
0 earthquake area.
Then, the topographic amplification ratio of the simulated ground motion is calculated.
Furthermore, a BP topographic amplification prediction model is established and compared based on different parameters.
A rms of less than or close to 10 per cent between the BP model prediction results and topographic amplification ratio calculated using the simulated ground motion suggests that the parameters of the topographic elevation, the first gradient of the elevation and the second-order gradient in two orthogonal directions are enough to provide the acceptable topographic effect model in the Lushan area.
Finally, using the prediction model, the topographic spectral ratio at stations 51BXD and 51BXM is predicted, and the topography amplification due to the scattering of seismic waves by the irregular topography at 51BXD is found to be 1.
5–2 times that of 51BXM.
The most important highlights of this paper identify the main factors of the topographic effect for the first time and provide an effective method for establishing a quantitative topographic effect prediction model.

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