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HVSR Survey Along the Wasatch Fault (Provo Segment)

Kathryn J. Smith ORCID
Coastal and Hydraulics Laboratory, U.S. Army Corps of Engineers Engineer Research and Development Center, Vicksburg, MS 39180, USA
John McBride ORCID
Department of Geological Sciences, Brigham Young University, Provo, UT 84602, USA
Stephen T. Nelson ORCID
Department of Geology and Geophysics, University of Utah, Salt Lake City, UT 84112, USA
Ronald A. Harris ORCID
Department of Geological Sciences, Brigham Young University, Provo, UT 84602, USA
Kevin A. Rey ORCID
Department of Geological Sciences, Brigham Young University, Provo, UT 84602, USA
Bo Worthen
Department of Geological Sciences, Brigham Young University, Provo, UT 84602, USA

Received: 13 September 2025; Revised: 27 October 2025; Accepted: 27 October 2025; Published: 14 November 2025

Abstract

The Wasatch Fault Corridor in northern Utah (USA) faces increasing seismic risks due to rising population density. Vs30 is a vital parameter for understanding how a site will respond to earthquake shaking; however, obtaining Vs30 can be costly or impractical because of infrastructure or access challenges. The horizontal-to-vertical spectral ratio (HVSR) enables rapid assessment, provided a relationship between Vs30 and the resonant frequency (f0) of the shallow subsurface can be established. Previously surveyed Vs30 sites in the Provo segment of the Wasatch Fault Zone were measured with a three-component seismometer to obtain f0. These sites are located on the hanging wall of the fault zone, within alluvial and lacustrine Quaternary sediments. For each of the 20 sites, ambient noise was recorded for 30 minutes and amplitude-frequency spectra computed for each component. A rubric was applied to select site results most suitable for analysis and forward modelling, based on uncertainty of f0, uncertainty of H/V response, and peak quality. The H/V response was then derived for 15 selected sites. The strongest low-frequency peak identified the f0, which ranged from 0.28 to 1.38 Hz. Experimenting with linear regression helps guide understanding of the potential for estimating Vs30 from HVSR in this region. 

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