Shear wave velocity (Vs) is one of the most important parameters of a geological model to assess the site effect and the ground response. In this paper the spatial variability of shear wave velocity in Mashhad capital...Shear wave velocity (Vs) is one of the most important parameters of a geological model to assess the site effect and the ground response. In this paper the spatial variability of shear wave velocity in Mashhad capital city are investigated. For this purpose, 243 Vs profiles of different projects throughout the city were used. Based on the Vs profiles the iso-level maps of the Vs interfaces 300, 500, 750, 950 and 1200 m/s were obtained by kriging interpolation method. The best semivariogram models were obtained with changing the effective parameters and assessing the components of the models and spatial dependence. The best models for the entire interfaces were exponential. Based on these models, the spatial dependence of depth data was moderate to strong. The performance of interpolations was checked by cross-validation and its indices?i.e. mean standardized prediction errors (MSPR), root mean square prediction errors (RMSPE), average kriging standard error (AKSE), and root mean square standardized prediction errors (RMSSPE) were assessed. A trend of depth increasing towards the northeast was observed at all of the interfaces.展开更多
文摘Shear wave velocity (Vs) is one of the most important parameters of a geological model to assess the site effect and the ground response. In this paper the spatial variability of shear wave velocity in Mashhad capital city are investigated. For this purpose, 243 Vs profiles of different projects throughout the city were used. Based on the Vs profiles the iso-level maps of the Vs interfaces 300, 500, 750, 950 and 1200 m/s were obtained by kriging interpolation method. The best semivariogram models were obtained with changing the effective parameters and assessing the components of the models and spatial dependence. The best models for the entire interfaces were exponential. Based on these models, the spatial dependence of depth data was moderate to strong. The performance of interpolations was checked by cross-validation and its indices?i.e. mean standardized prediction errors (MSPR), root mean square prediction errors (RMSPE), average kriging standard error (AKSE), and root mean square standardized prediction errors (RMSSPE) were assessed. A trend of depth increasing towards the northeast was observed at all of the interfaces.
