Earth, Planets and Space (May 2023)

Regional terrain-based V S30 prediction models for China

  • Yuting Zhang,
  • Yefei Ren,
  • Ruizhi Wen,
  • Hongwei Wang,
  • Kun Ji

DOI
https://doi.org/10.1186/s40623-023-01826-3
Journal volume & issue
Vol. 75, no. 1
pp. 1 – 19

Abstract

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Abstract Time-averaged shear-wave velocity to 30 m (V S30) is commonly used in ground motion models as a parameter for evaluating site effects. This study used a collection of boreholes in Beijing, Tianjin, Guangxi, Guangdong, and three other municipalities and provinces, which were divided into three regions with reference to the seismic ground motion parameter zonation map of China, to establish V S30 prediction models based on terrain categories. Regional effects were verified by comparing morphometric parameter (topographic slope, surface texture, and local convexity) thresholds and terrain classification maps obtained from global digital elevation model (DEM) data and regional DEM data of the three regions. Additionally, V S30 prediction models for the three regions using both types of terrain classification maps were established and analyzed comparatively to provide credible regional V S30 models for China. Through analysis of the correlations between the measured V S30 values and the predicted V S30 values, calculation of the mean squared error and mean absolute percentage error in each region, and with consideration of the geological characteristics of the boreholes, the V S30 prediction models based on terrain classification maps from regional data were finally applied in developing regional V S30 models for China. Intercomparison of the V S30 prediction models for the three regions indicated that subregional consideration is necessary in terrain classification. Finally, a spatial analysis method adopting inverse distance weighting of the residuals was used to update the initial V S30 models. The developed V S30 models could be used both in developing regional ground motion models and in the construction of earthquake disaster scenarios. Graphical Abstract

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