The correlation of peak ground horizontal acceleration with magnitude, distance, and seismic intensity for Friuli and Ancona, Italy, and the Alpide Belt

Abstract

Abstract A new sample of strong-motion data has been analyzed in this paper: namely 120 records from the 1976 Friuli earthquake, 40 from the 1972 Ancona swarm, and 64 from different Alpide Belt shocks. The sample is the result of the selection of peak recorded horizontal acceleration of every three-component record greater than 0.015 g. Linear regressions were applied to the data with the purpose of understanding the geography and the site-dependence. Separate analyses have been carried out, firstly taking into account acceleration (a), magnitude (ML), and distance (d), then computing a - IMM relationships and comparing the respective standard errors of the estimates. Finally, a - ML - d - IMM regressions for the total sample from Friuli, Ancona, and the Alpide Belt have been computed. The main result are The Friuli data are 70 per cent lower than those of the Alpide Belt and Ancona. The Ancona set of data is closely related to the Alpidic set, at a magnitude level of 4.0. The expected accelerations in Friuli are close to the average values recorded in the Circumpacific Belt region (intermediate earthquakes excluded), while the Alpide Belt accelerations are close to the Circumpacific maxima. Site-dependence between data recorded in Friuli on thick consolidated alluvium (ThA) and on rock-like (RI) is not statistically significative. Friuli sites with thin alluvium (thA) exhibit stronger average accelerations and a significant difference in the ML coefficient (which is 0.47, with a standard error of 0.05) as regards the RI + ThA category (which has a value of 0.35, with a standard error of 0.04). The standard errors of the estimates of the regressions a - IMM in the case of Friuli and the Alpide Belt are close to the corresponding standard errors of the regressions a - ML - d. It may be concluded that a - IMM correlations are, in some cases, a valuable tool for seismic risk estimations, especially for being able to use the historical information.