GNGTS 2024 - Atti del 42° Convegno Nazionale

Session 2.2 GNGTS 2024 Using data from CRISP database to infer site response behaviour G. Cultrera 1 , A. Mercuri 1 (1) Is9tuto Nazionale di Geofisica e Vulcanologia, Roma - Italy The CRISP archive is a web portal that collects site informaCon of the Italian NaConal Seismic Network RSN (website crisp.ingv.it ; Mercuri et al., 2023). It is organized to contain all the informaCon useful for the site characterizaCon, such as: themaCc maps on geological characterisCcs; informaCon on staCon and housing (locaCon, instrumentaCon, data quality, housing type); geological data under and around the staCon (straCgraphy, geological review, morphological, lithological and geological classificaCon, cross secCon); seismic analysis on recordings (spectral raCo on noise and earthquake, signal polarizaCon); geophysical invesCgaCons (Vs profile, non linear curve); topography and soil class. CRISP is populated with heterogeneous data coming from pre-exisCng INGV archives or having different origins, such as: maps and geological descripCon from ISPRA ( hbps://www.isprambiente.gov.it/) , results of seismological analyses and geophysical surveys specifically performed or inferred from literature, site and topography classificaCon using different available informaCon. It represents a conCnuously expanding database being updated with new staCons added to the naConal network and with new data gradually becoming available from new sources. With 340 staCons present at the beginning of 2023, in the framework of the naConal research PRIN project SERENA - Mapping Seismic Site Effects at REGional and NATIONAL Scale, (WP6 - Empirical TesCng and CalibraCon) CRISP represents a good starCng point for systemaCsing the informaCon related to the site characterizaCon with the aim to idenCfy a site amplificaCon model based on site condiCon indicators. A preliminary selecCon of representaCve proxies drove us to extract and compare the indicators related to the morphological and lithological classificaCon, site classificaCon and seismological analysis. Specifically, we selected the slope of morphology, lithological type, soil consolidaCon degree, amplitude and frequency peaks of Horizontal-to-VerCcal spectral raCo (HVSR) on noise and earthquakes, frequency and direcCon of polarizaCon, topography class and site class from EC08 and NTC18. In order to idenCfy the significant indicators and recognize their dependencies, we first analysed the distribuCon of each indicator (see histograms of Lithological classificaCon groupments and site class in Fig.1).