The potential of spatial statistics for the reconstruction of a subsoil model: A case study for the Firenze-Prato-Pistoia Basin, Central Italy

A reliable subsoil model represents the first step in assessing potential geological hazards and adopting proper mitigation measures accordingly. However, one of the main difficulties related to the definition of such models concerns the extrapolation of single-point data over wide, uninvestigated areas. For this reason, in this work, we reconstruct a subsoil model within an alluvial basin through a methodology specifically based on spatialstatistical analyses of geophysical in situ point measurements. In particular, measurements of ambient noise were analysed and extrapolated to obtain a spatially continuous distribution of fundamental resonance frequency (f0) over the entire basin. Local portions of the basin were then defined according to a specific relationship between f0 and the minimum distance from the bedrock outcrops (MDBO). This analysis revealed how the position of the identified clusters is consistent with the asymmetric geometry of the basin. The resulting simplified subsoil model was then validated through additional experimental measurements of ambient noise to evaluate the reliability of the proposed methodology. As the test site, we selected the Firenze-Prato-Pistoia Basin (Tuscany region, central Italy), where more than two hundred homogeneously distributed noise measurements were collected from previous seismic microzonation investigations.