AUTHOR=Liu Jia Mei , Zhang Bin , Zhao Xu Dong 

TITLE=Empirical relationships between Arias Intensity and peak ground acceleration for western China

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2024.1434194

DOI=10.3389/feart.2024.1434194

ISSN=2296-6463

ABSTRACT=We establish empirical relationships for Arias Intensity (AI) and peak ground acceleration (PGA) for western China, utilizing 3169 horizontal and 979 vertical strong motion records with PGA ≥ 0.01g from 274 earthquakes (M S 4.0-8.0), originating in eight provinces in southwest (Yunnan, Sichuan) and northwest China (Gansu, Shaanxi, Ningxia, Qinghai, Inner Mongolia, and Xinjiang). The influences of M S and epicenter distance are validated. The dependence on V S30 and generic site classes (i.e. rock and soil) is explored. The results confirm that the logarithm of AI increases linearly with the increase of the logarithm of PGA and M S , and decreases with the logarithm of V S30 . However, the influence of site conditions on AI-PAG relationships can't be recognized by the simple generic rock and soil site classes. The epicenter distance has little effect on the AI-PAG relationships. Empirical relationships are developed to estimate horizontal or vertical AI as a function of PGA (basic model), PGA and M S (model 2) for southwest, northwest, and western China, using all the records. Empirical relationships for AI as a function of PGA, M S , and V S30 (model 1) are established using the 2248 horizontal (70.9% of the total) and 670 vertical (68.4% of the total) records with V S30 . The notable disparity between model 1 of the southwest and northwest regions indicates that the AI-PGA correlation is region-dependent. This region-dependent effect is chiefly attributed to local site conditions. We consider our new models to be applicable for M S ranging from 4.0 to 8.0, V S30 between 148 and 841m/ s and PGA ≥ 0.01g. They enable one way of estimating AI from PGA for western China and will also enhance the understanding of AI attenuation.