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A statistical approach to account for azimuthal variability in single-station HVSR measurements.
- Source :
- Geophysical Journal International; Nov2020, Vol. 223 Issue 2, p1040-1053, 14p
- Publication Year :
- 2020
-
Abstract
- The horizontal-to-vertical spectral ratio (HVSR) of ambient noise is commonly used to infer a site's resonance frequency (|${f_{0,site}}$|). HVSR calculations are performed most commonly using the Fourier amplitude spectrum obtained from a single merged horizontal component (e.g. the geometric mean component) from a three-component sensor. However, the use of a single merged horizontal component implicitly relies on the assumptions of azimuthally isotropic seismic noise and 1-D surface and subsurface conditions. These assumptions may not be justified at many sites, leading to azimuthal variability in HVSR measurements that cannot be accounted for using a single merged component. This paper proposes a new statistical method to account for azimuthal variability in the peak frequency of HVSR curves (|${f_{0,HVSR}}$|). The method uses rotated horizontal components at evenly distributed azimuthal intervals to investigate and quantify azimuthal variability. To ensure unbiased statistics for |${f_{0,HVSR}}$| are obtained, a frequency-domain window-rejection algorithm is applied at each azimuth to automatically remove contaminated time windows in which the |${f_{0,HVSR}}$| values are statistical outliers relative to those obtained from the majority of windows at that azimuth. Then, a weighting scheme is used to account for different numbers of accepted time windows at each azimuth. The new method is applied to a data set of 114 HVSR measurements with significant azimuthal variability in |${f_{0,HVSR}}$| , and is shown to reliably account for this variability. The methodology is also extended to the estimation of a complete lognormal-median HVSR curve that accounts for azimuthal variability. To encourage the adoption of this statistical approach to accounting for azimuthal variability in single-station HVSR measurements, the methods presented in this paper have been incorporated into hvsrpy , an open-source Python package for HVSR processing. [ABSTRACT FROM AUTHOR]
- Subjects :
- AZIMUTH
ACCOUNTING methods
ALGORITHMS
TIME series analysis
Subjects
Details
- Language :
- English
- ISSN :
- 0956540X
- Volume :
- 223
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Geophysical Journal International
- Publication Type :
- Academic Journal
- Accession number :
- 147074615
- Full Text :
- https://doi.org/10.1093/gji/ggaa342