Site Amplification Factors for the Walnut Creek and Concord Regions of the San Francisco Bay, California

This data release contains rasterized data sets of point values of site amplification for the Walnut Creek and Concord regions of the San Francisco east bay. Hartzell et al. (2024) covers the associated field work and the source-site inversion method used to obtain the site response spectra. Site amplification values are given for the geometric average over four frequency ranges (0.5 to 1 Hz, 1 to 2 Hz, 2 to 4 Hz, and 4 to 6 Hz) and two ground-motion data sets. The two data sets consist of earthquakes recorded for a two-year period from 2017 to 2019 for the two cases: (1) earthquakes whose epicenters fall within 10 km of the center of the study area, and (2) all well-recorded local earthquakes regardless of distance. The second case leads to greater amplification over a larger area due to increased surface wave development from the more distant sources. Site response spectra were obtained at 37 stations distributed across the study area. The geometric average values within the selected frequency bands are spatially interpolated using the natural neighbor scheme of Sibson (1981). The interpolation algorithm uses only a subset of samples that surround a query point, and interpolated values are guaranteed to be within the range of the samples used. It does not infer trends and will not produce peaks, pits, ridges, or valleys that are not already represented by the input samples. Figures 1 and 2 in the attached files section show images of the rasterized values for the two data sets.

Reference List:
 
     Hartzell, S., Leeds, A.L.,Ramirez-Guzman, L., Langenheim, V., and Schmitt, R.G., 2024, Site Response in the Walnut Creek–Concord Region of San Francisco Bay, California: Ground‐Motion Amplification in a Fault‐Bounded Basin: Bulletin of the Seismological Society of America, 114 (5): 2668–2686, https://doi.org/10.5066/P13CUTBU
     Sibson, R., 1981, A Brief Description of Natural Neighbor Interpolation: Barnett, V., Ed., Interpreting Multivariate Data, John Wiley & Sons, New York, 21-36.