Abstract
The HVSR method applied to seismic noise can be a very useful technique to map the site effects of the territory, to identify the thickness of the soft covering and so the depth of the seismic bedrock. The case of the urban area of Oliveri is presented. Because of its high seismic hazard this area has been subject of first level seismic microzonation. The town lies on a large coastal plain made of mixed fluvial/marine sediments, overlapping a deformed substrate. In order to identify points on the area probably suffering of relevant site effects and to define a preliminary Vs subsurface model, 23 HVSR measurements were performed. A clustering technique of continuous signals has been used to optimize the calculation of the HVSR curves and 42 reliable peaks, in the frequency range 0.1-20 Hz, have been identified. A second clustering technique has been applied to the set of 42 vectors, containing coordinates, frequency and amplitude of each peak, to identify subsets attributed to the same seismic discontinuities. Three main clusters have been identified. The two characterized by lower frequencies have been considered in the HVSR data inversion, as stratigraphic peaks probably caused by the seismic bedrock. Finally, the morphology of the top of the seismic bedrock has been mapped. The deepening of the seismic bedrock below the mouth of the Elicona Torrent suggests the possible presence of a buried paleo-valley.
Highlights
The seismic microzonation of a territory aims to recognize the small scale geological and geomorphological conditions that may significantly affect the characteristics of the seismic motion, generating high stress on structures and produce permanent and critical effects [Ben-Menahem and Singh, 1981; Yuncha and Luzon, 2000].The dynamic characteristics of a seismic phase of body or surface waves, generated by an earthquake and incident on a portion of the ground surface, often show sharp variations
The use of techniques of cluster analysis in the seismic noise processing, based on an Agglomerative Hierarchical Clustering (AHC) algorithm, allowed to separate the noise windows in clusters with spectral effects due to subsurface structures and clusters dominated by accidental interference effects between wave trains of a different nature
The average spectral ratio of the cluster dominated by structural effects is generally characterized by smaller variance of the frequencies and amplitudes of the significant peaks, compared to those of the peaks determined with standard methods
Summary
The seismic microzonation of a territory aims to recognize the small scale geological and geomorphological conditions that may significantly affect the characteristics of the seismic motion, generating high stress on structures and produce permanent and critical effects (site effects) [Ben-Menahem and Singh, 1981; Yuncha and Luzon, 2000]. The dynamic characteristics of a seismic phase of body or surface waves, generated by an earthquake and incident on a portion of the ground surface, often show sharp variations Such variations are frequency dependent and sometimes have extremely local character. Significant increases of peak amplitude of ground shaking are commonly called site effects [Bonnefoy-Claudet et al, 2006b] These phenomena are controlled by anomalies in the mechanical properties of the shallowest layers of the subsoil, especially when it consists of soft sediments, or by the shape of the topographic surface. Not necessarily an HVSR peak must be attributed to resonance frequencies of a buried structure It might depend on the sources of noise and in such case it will be not correlated with amplification effects on incident waves [Bonnefoy-Claudet et al, 2006b; Kurtulmuş & Akyol, 2015]. In zones where stratigraphic drillings are available, a good practice is to constrain HVSR inversion by fixing thickness of near surface layers detected by drilling [Amorosi, 2008; Grippa et al, 2011; Tropeano et al, 2013] and by adding deeper seismic layers to interpret peaks of lower frequencies [Castellaro & Mulargia, 2009, Martorana et al, 2018]
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