Production of GIS-Based Predicted Vs30 Maps for Türkiye by Combining Geological and High-Resolution Topographical Digital Maps


Şahin G., Okalp K., Koçkar M. K., Yılmaz M. T., Jalehforouzan A., Temiz F. A., ...More

7th International Conference on Earthquake Engineering and Seismology, 7ICEES 2023, Antalya, Turkey, 6 - 10 November 2023, vol.488 LNCE, pp.167-174 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 488 LNCE
  • Doi Number: 10.1007/978-3-031-57659-1_12
  • City: Antalya
  • Country: Turkey
  • Page Numbers: pp.167-174
  • Keywords: Geology, Regression analysis, Seismic hazard, Topography, Türkiye, Vs30 map
  • Middle East Technical University Affiliated: Yes

Abstract

Vs30 is an important field parameter in determining the intensity of ground shaking and characterizing local soil conditions for estimating site effects to determine seismic hazards. Given the critical need for acquiring Vs30 values, particularly in a digital format and on a grid scale, a comprehensive study to estimate Vs30 all across Türkiye has become essential. Therefore, in this study, relationships between Vs30, geological and topographical data have been investigated, and empirical equations to estimate Vs30 values have been established. These relationships have been developed based on data obtained from the digital geological and digital topographic elevation maps (MERIT-DEM), and Vs30 measurements near the vicinity of strong ground motion stations all across Türkiye. Units in digital geological maps were initially regrouped into classes based on geological periods. The correlations between these classes and the Vs30 samples were interpreted to determine the limits of each class. Secondly, topographic parameters were calculated with 2D trend surface analysis methods to be used in Vs30 predictions. The topographical parameters were correlated with Vs30 utilizing the least-squares method, resulting in the generation of equations for estimating Vs30 for each geological category (R2: 0.601). In addition, the coefficients of the envelope curve corresponding to a given exceedance probability (p) for the worst-case scenario were determined using the quantile regression method. Consequently, digitized maps of the Vs30 estimations were produced in a raster format that can be queried in a GIS environment.