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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.

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<p>Shear wave velocity, V_s, is one of the important input parameters in seismic response analysis of the ground. Various methods have been examined to measure the soil V_s directly. Direct measurement of V_s is time consuming and costly, therefore many researchers have been trying to update empirical relationships between V_s and other geotechnical properties of soils such as SPT Blow count, SPT-N. In this study the existence of a statistical relationship between V_s, SPT-N₆₀and vertical effective stress, signa_nu´, is investigated. Data set we used in this study was gathered from geotechnical and geophysical investigations reports. The data have been extracted from more than 130 numbers of geotechnical boreholes from different parts of Mashhad city. In each borehole the V_s has been measured by downhole method at two meter intervals. The SPT test also has performed at the same depth. Finally relationships were developed by regression analysis for gravels, sands and fine grain soils. The proposed relationships indicate that V_s is strongly dependent on signa_nu´. In this paper the effect of fine percent also is considered on the V_s estimation.</p>