GNGTS 2013 - Atti del 32° Convegno Nazionale

problem can be predicted and solved studying the ellipticity. The use of multichannel, passive single station data and multicomponent active multichannel data can be a practical solution. Multi-component surface wave data. Passive data. Site characterization techniques base on the spectral relationship between horizontal and vertical components of ambient noise have become very popular, being fast and efficient especially in mapping and zonation projects. The Horizontal to Vertical Spectral Ratio (HVSR) has been proven to be an efficient detector of impedance contrasts, even if the nature of the spectral peaks is still debated. Even neglecting the intricacies of the λ/4 hypothesis (Konno and Omachi, 1988; Lachet and Bard, 1994; Chatelain et al. , 2007), body wave contribution and HVSR amplitude interpretation (Bard, 1998), measurements of single station noise is certainly capable of excluding or confirming the presence of a strong impedance contrast (Bonnefoy- Claudet et al. , 2008). Consequently, single station noise measurements can also be useful in the identification of a subsoil that can induce modal misidentification in surface wave dispersion study. It has been proven that, under some hypotheses (or conditions) the average spectral ratio is a reliable measure of the Rayleigh wave ellipticity (Hobiger et al. , 2009; Malischewsky and Scherbaum, 2004). With strong velocity contrasts, and with near sources of ambient noise, the noise wavefield is dominated by surface waves, and the spectral ratio can be considered as an experimental ellipticity curve. We created some simple synthetic ReMi data, using a model with 5 m of sediments (Vs=300 m/s) over a bedrock of (Vs=1100 m/s). The source distribution is random and uniform in azimuth around a linear array, composed of 48 channels, spaced 2 meters. The resulting frequency-normalized ReMi spectrum is shown in Fig. 2. The generation of pure Rayleigh wave data and the computation of the spectrum follow the approach of Strobbia and Cassiani (2011). We notice that at the osculation point, the different energy ratio between the two modes changes the shape of the averaged spectrum. The peak becomes closer to the higher mode, due to the effect of the energy shift, but the spectrum is more skewed. The inspection of two slices at constant frequency, at 23 Hz and 28 Hz, above and below the osculation frequency, shows the relationship between the spectral maxima and the true wavenumber of the fundamental and higher modes (Figs. 2b and 2c). If some evidence of lower velocity is present, the ambiguities Fig. 2 – F-K analysis of synthetic ReMi f-k spectrum generated with 5000 sources uniformly and randomly distributed around a linear 48 channels with 2 m spacing array for (5 m of sediments with Vs =300 m/s over a bedrock of Vs=1100 m/s). Two slices at 28 Hz and 23 Hz are plotted respectively in panels b) and c). Below the osculation frequency the peak of the spectrum is closer to mode2, thus also these ReMi data suffer from the osculation problem. 25 GNGTS 2013 S essione 3.1