Summary. Proceeding on the assumption that the seismic noise wavefield mainly consists of surface waves generated by a random distribution of independent, poin

In earthquake engineering, “engineering bedrock” is regarded as a stiff material (i.e., rock or rock‐like geological formation) that is characterized by a shear‐wave velocity greater than a target value (e.g., $800m/s$⁠; current Italian and European seismic codes). In the case of deep basins, the identification of engineering bedrock is problematic, because it can lie well below the penetration depth of most common prospecting methods (i.e., a few tens of meters). Moreover, the depth of engineering bedrock might not represent an effective proxy of the sedimentary thickness responsible for site amplification. The Po Plain sedimentary basin (northern Italy) is one of the deepest and widest worldwide, and it presents such problems. The aim of this work is to estimate the sedimentary thickness responsible for ground‐motion amplification at medium and long periods in the Po Plain. Passive seismic prospecting methods based on ambient‐vibration measurements using single‐station and array configurations were considered to map “seismic bedrock” depth. This corresponds to a marked seismic impedance contrast where the shear‐wave velocity approached, or exceeded, $800m/s$⁠. In the latter case, seismic and engineering bedrocks coincided. Our mapping will be useful for future site response assessments, numerical modeling of seismic‐wave propagation, dynamic ground response analyses, and site‐specific seismic hazard evaluation at the basin scale.

Summary. An evaluation of the actual reliability of probabilistic seismic hazard (PSH) assessments, provided by existing numerical techniques, is mandatory to

The evaluation of seismic hazard over wide territories is a basic tool for planning activities aimed at earthquake damage mitigation. This is commonly performed through probabilistic approaches based on the statistical analysis of past seismicity. Among these, due to its wide application worldwide, the Cornell-McGuire approach (Cornell 1968; McGuire 1978) has become a kind of “standard” methodology for probabilistic seismic hazard assessment (PSHA). In Italy, several national seismic hazard maps were produced in recent years (Slejko et al. 1998; Albarello et al. 2000; MPS Working Group 2004) by following this procedure as implemented by Bender and Perkins (1987). Yet despite its widespread application, this standard methodology presents severe drawbacks due to its strong sensitivity to some ill-defined aspects, such as geometry of seismic sources, attenuation of ground motion with distance from the source, completeness of available seismic catalogs, etc. Moreover, this kind of approach does not allow the full exploitation of a large amount of documentary data available at the site about the seismic effects of past earthquakes (Albarello and Mucciarelli 2003). Another drawback is that the standard approach was developed with the assumption that the seismicity database used to feed the computational model is constituted by instrumental data (magnitude, epicentral locations, etc.). However, in many countries (first and foremost, Italy) the bulk of the seismic database is constituted by macroseismic data, and thus the application of the standard method requires a “forcing” of macroseismic information into a para-instrumental format. But macroseismic information is not isomorphic to instrumental data since intensity values are discrete, ordinal, and range-limited. This implies that, in principle, mathematical formalizations suitable to instrumental information cannot be used to manage macroseismic data (see, e.g., Pasolini et al. 2008a, 2008b). To overcome some of these difficulties and to better exploit available information, probabilistic hazard evaluations based on observed intensity data were performed in Europe (Monachesi et al. 1994; Papoulia and Slejko 1997; Azzaro et al. 1999; Albarello et al. 2002) and Japan (Bozkurt et al. 2007) using alternative numerical procedures. An apparent limitation of these studies is the fact that PSH estimates are provided in terms of intensity, and this conflicts with the fact that ground acceleration still remains the traditional output of PSHA devoted to seismic design. However, a new interest has recently grown around macroseismic intensity. In fact, when damage scenarios and post-earthquake emergency planning are of concern, hazard assessment in terms of intensity as ground-shaking measure may be more suitable than conventional estimates based on instrumental parameters (PGA, etc.). A further possible advantage of these kinds of approaches is that they provide hazard evaluations completely independent from the standard ones and more directly linked to empirical observations (local seismic history). Thus, they could represent a useful benchmark for a direct assessment of reliability of traditional PSH estimates (Mucciarelli et al. 2000, 2006, 2008; Bozkurt et al. 2007). In this paper we present the computer program SASHA (Site Approach to Seismic Hazard Assessment), which implements the intensity-based PSHA procedure originally proposed by Magri et al. (1994) and then improved by Albarello and Mucciarelli (2002). It relies on the analysis of the site seismic history, i.e., the dataset of seismic effects (macroseismic intensities) documented during past earthquakes at a given locality. This methodology (hereafter, site approach) has been specifically developed to handle macroseismic data, and thus both the peculiar nature of intensity values (discrete, ordinal, range-limited) and relevant uncertainty (ill-defined intensity values, completeness of site seismic history, etc.) are taken into account by a coherent statistical approach that does not require any assumption about earthquake recurrence model and seismic source geometry. Furthermore, no aftershock removal is required in advance and epicentral data are only considered to integrate (when necessary) felt data at the site. Several PSHA studies have been performed in the last decade in Italy using different versions of the site approach (Mucciarelli et al. 2000; Albarello et al. 2002; D’Amico and Albarello 2003; Albarello, Azzaro et al. 2007; Azzaro et al. 2008). SASHA’s theoretical background is briefly outlined in the next section of the paper. Then, we describe the most important features of SASHA along with a sample application to the Italian area