{"title":"Characterizing uncertainty in shear wave velocity profiles from the Italian seismic microzonation database","authors":"Federico Mori, Giuseppe Naso, Amerigo Mendicelli, Giancarlo Ciotoli, Chiara Varone, Massimiliano Moscatelli","doi":"10.5194/essd-2024-104","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> This research uses a large dataset from the Italian Seismic Microzonation Database, containing nearly 15,000 measured shear wave velocity (Vs) profiles across Italy, to investigate the uncertainties in seismic risk assessment. This extensive collection allows a detailed study of the seismic properties of soil with unparalleled precision. Our focus is on evaluating Vs variations with depth within uniformly clustered areas, known as seismic microzones. These zones are carefully identified based on their spatial correlation and homogeneity in geological, geophysical, and geotechnical characteristics, which are critical for accurate prediction of seismic response. We contrast these results with clusters formed purely based on geographic survey density (here defined geographic clusters), thereby assessing the depth of our understanding of the subsurface geological and geophysical context. These results were further compared with those reported in the seismic code and literature. This study of depth-dependent Vs variations helps to refine our models of subsurface seismic behaviour. Our main discoveries show that: 1) uncertainties associated with seismic microzones (geological and geophysical clusters) are consistently lower than those identified in geographic clusters, particularly in the first 30 m of depth; 2) Vs profile variations show negligible increases in uncertainty within a certain range of correlation distances (up to about 4,500 m); 3) uncertainties for seismic microzones are lower than those previously reported in seismic codes and in the literature, indicating the effectiveness and precision of our methodological approach. The results of this study significantly improve local seismic response analysis and highlight the critical role of depth and spatial correlation in understanding seismic hazard. The dataset is available at https://doi.org/10.5281/zenodo.10885590 (Mori et al., 2024).","PeriodicalId":48747,"journal":{"name":"Earth System Science Data","volume":"31 1","pages":""},"PeriodicalIF":11.2000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth System Science Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/essd-2024-104","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. This research uses a large dataset from the Italian Seismic Microzonation Database, containing nearly 15,000 measured shear wave velocity (Vs) profiles across Italy, to investigate the uncertainties in seismic risk assessment. This extensive collection allows a detailed study of the seismic properties of soil with unparalleled precision. Our focus is on evaluating Vs variations with depth within uniformly clustered areas, known as seismic microzones. These zones are carefully identified based on their spatial correlation and homogeneity in geological, geophysical, and geotechnical characteristics, which are critical for accurate prediction of seismic response. We contrast these results with clusters formed purely based on geographic survey density (here defined geographic clusters), thereby assessing the depth of our understanding of the subsurface geological and geophysical context. These results were further compared with those reported in the seismic code and literature. This study of depth-dependent Vs variations helps to refine our models of subsurface seismic behaviour. Our main discoveries show that: 1) uncertainties associated with seismic microzones (geological and geophysical clusters) are consistently lower than those identified in geographic clusters, particularly in the first 30 m of depth; 2) Vs profile variations show negligible increases in uncertainty within a certain range of correlation distances (up to about 4,500 m); 3) uncertainties for seismic microzones are lower than those previously reported in seismic codes and in the literature, indicating the effectiveness and precision of our methodological approach. The results of this study significantly improve local seismic response analysis and highlight the critical role of depth and spatial correlation in understanding seismic hazard. The dataset is available at https://doi.org/10.5281/zenodo.10885590 (Mori et al., 2024).
Earth System Science DataGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
18.00
自引率
5.30%
发文量
231
审稿时长
35 weeks
期刊介绍:
Earth System Science Data (ESSD) is an international, interdisciplinary journal that publishes articles on original research data in order to promote the reuse of high-quality data in the field of Earth system sciences. The journal welcomes submissions of original data or data collections that meet the required quality standards and have the potential to contribute to the goals of the journal. It includes sections dedicated to regular-length articles, brief communications (such as updates to existing data sets), commentaries, review articles, and special issues. ESSD is abstracted and indexed in several databases, including Science Citation Index Expanded, Current Contents/PCE, Scopus, ADS, CLOCKSS, CNKI, DOAJ, EBSCO, Gale/Cengage, GoOA (CAS), and Google Scholar, among others.