Abstract.A simultaneous inversion for threedimensional velocity structure and hypocentral parameters is used to determine the tomographic images of the backarc of Kyushu, southwestern Japan. The data used in the imaging are the first arrival times of 2736 local earthquakes recorded at 305 stations in a wide regicn from western Japan to eastern China. Additional data are provided by including arrival times of 357 teleseismic earthquakes. We got the high resolution of the uppermost mantle images for P waves at least in the depth range to 150 km, the latitude range of 30ø-34øN and the longitude range of 128ø-132øE. Results of inversion reveal a major zone of strong low velocity under west off Kyushu Island in the depth from 40 km to 100 km. This feature may result from partially melting in relation to the upwelling of hot mantle around the northeastern edge of the extending Okinawa trough.

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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>

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