A Ground-truth Database for Central China

We have constructed a ground-truth database consisting of phase-picks data and other geological and geophysical information in Sichuan and Yunnan Provinces in central China. The database includes 1,600 regional seismic events with over 40,000 phase picks recorded by the regional seismic network in central China from 1985 to 1994. The distribution of the seismic events covers the area 97E to 108E and 20N to 40N, with magnitudes ML= 0.3-6.9 and a maximum depth of 41 km. The data listing in the database is raw data information and contains a comprehensive listing of all phases that were detected. The listed information of the earthquakes includes origin time, epicenter location, magnitude, and focal depth. Major phase picks, such as Pn, Pg, Sg, were reported. Quality control is performed on the raw data, and unreliable picks are discarded. The data are compiled and stored in CSS format. The flat file tables include the origin, arrival, association, and site tables. As part of the effort to construct a comprehensive ground-truth database of central China, other geological and geophysical information such as the seismogenic structure in central China, is also included. This data set forms the basis of an initial input to a ground-truth database for central China and has been delivered for incorporation into the Knowledge Base developed by the Department of Energy. Analysis of the data has been performed to yield a preliminary velocity model in central China. We performed a three-dimensional (3-D) tomographic inversion in central China by using the phase-picks data in the database. Altogether, 372 events are selected with over 5,900 P-phase arrivals. A five-layer 1-D starting model is chosen according to previous studies in the region. The studied region is divided into 16 by 16 blocks with a resolution of 0.5 degree. A 63% reduction in data variance is achieved after the fifth iteration of the joint inversion of crustal structure with relocation of the events. The results show correlation between the topography and the crustal velocity structure. The resultant crustal model also improves the clustering pattern of the seismic events in the region.