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On the Identification of Industrial Components in the Horizontal-to-Vertical Spectral Ratio (HVSR) from Microtremors

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Abstract

In seismic hazard studies, the Horizontal-to-Vertical Spectral Ratio (HVSR) is nowadays routinely considered as a quick way to assess possible amplification effects. However, because of several issues that can affect the data, the HVSR cannot be considered as valid per se, and a careful data evaluation is necessary. In this study, a series of HVSR curves are evaluated in order to highlight industrial components that can significantly alter the natural HVSR. First, a controlled-source experiment is carried out in order to define the characteristics of spurious industrial signals. Data analysis shows that the coherence functions and the mildly smoothed amplitude spectra plotted with linear scales can help significantly in identifying industrial components that can be otherwise difficult to highlight. Coherence functions appear particularly interesting because of their ability to reveal the presence of industrial components independently of their amplitude. Field data from three sites are then analyzed on the basis of the evidence obtained through the controlled-source experiment. For the third site, data recorded on two different days are considered. While in the first data set no significant industrial component is present, in the second and third data sets, a series of remarkable industrial signals that severely alter the natural HVSR are identified. The assessment of the coherence functions and mildly smoothed amplitude spectra is therefore suggested as a valuable support to avoid pitfalls in the interpretation of the experimental HVSR. Finally, two quick and dirty procedures aimed at reducing the effect of industrial components are also presented.

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Acknowledgements

This work was supported in part by the Institute of Rock Structure and Mechanics (Czech Academy of Sciences, Prague, CZ) in the framework of the long-term conceptual development project RVO 67985891 (Institute grant for the “Extreme Seismics” project). The author is also grateful to two anonymous reviewers for their several helpful comments and suggestions.

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  1. Department of Seismotectonics, Institute of Rock Structure and Mechanics (Academy of Sciences of the Czech Republic), V Holesovickach 94/41, 18209, Prague 8, Czech Republic

    Giancarlo Dal Moro

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Appendix: Two Simple Ways to Attenuate Industrial Components in the HVSR Curve

Appendix: Two Simple Ways to Attenuate Industrial Components in the HVSR Curve

In this section, the site #2 data are used to briefly illustrate two possible simple (quick and dirty) ways of handling HVSR curves altered by significant industrial components.

Since in such a data set the effect of the 1.5-Hz industrial component is particularly clear and distinguishable from the natural background microtremor field (see Figs. 9, 10 and 11), it is possible to try to compute the HVSR after having manually interpolated (picked) the mean amplitude spectra of the three (UD, NS and EW) components. Figure 21 summarizes the results obtained when following this approach. The upper plot (Fig. 21a) shows the original amplitude spectra (5% smoothing, thin lines) and the manually interpolated (picked) spectra obtained by simply ignoring the large 1.5-Hz spurious peaks (thick lines). In the lower plot (Fig. 21b), the HVSR curves from the original raw data (thin line) and from the picked amplitude spectra (thick line) are presented.

Fig. 21
figure 21

Site #2: reconstruction of the HVSR through the picking of the mean amplitude spectra: a mean amplitude spectra obtained by applying a 5% smoothing (thin lines) and picked while bypassing the 1.5-Hz industrial peaks (tick lines) [red: UD; green: NS; blue: EW]; b HVSR obtained by considering the original (5% smoothed) amplitude spectra (thin line) and by computing the H/V ratio from the picked amplitude spectra shown in the upper plot (thick line)

Full size image

Because of the small (5%) smoothing, the HVSR peak obtained from the raw data (thin line in Fig. 21b) is larger than that obtained when using a 15% smoothing (as usually applied for the computation of the HVSR; compare Fig. 21b with Fig. 9b).

Since the 1.5-Hz signal is so well-defined (quasi-monochromatic signal), while the rest of the spectra are quite smooth, in order to smooth the 1.5-Hz spurious peak, we might also try a different (and quite brutal) approach: increasing the spectral smoothing to a very high level. Figure 22 shows the amplitude spectra and HVSR curve when adopting 90% spectral smoothing.

Fig. 22
figure 22

Site #2: a mean amplitude spectra for the UD, NS and EW components when applying 90% smoothing; b mean HVSR curve and standard deviations

Full size image

For this kind of data (spectra), the two approaches provide similar (but not identical) results. In both cases, the H/V peak decreases from the original value of 12.5 (Fig. 9b) to about 4–4.5 (Figs. 21b, 22b).

Clearly, both of these approaches (and particularly the second) are quite crude and are presented just to show how large the peaks produced by industrial components can be and how to possibly handle them in case the latter are well-characterized with respect to the background natural microtremor field (it must be considered that a notch filter cannot be applied, because it would also remove the part of the signal which is related to the natural microtremor field).

Note that the two approaches are applied to the final mean curves (so in the frequency domain) and can be considered simply as quick and dirty techniques aimed at obtaining a gross estimate of the HVSR due to the natural microtremors only.

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Dal Moro, G. On the Identification of Industrial Components in the Horizontal-to-Vertical Spectral Ratio (HVSR) from Microtremors. Pure Appl. Geophys. 177, 3831–3849 (2020). https://doi.org/10.1007/s00024-020-02424-0

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