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The destructive 2023 moment magnitude ( M w ) 7.8-7.7 earthquake doublet ruptured multiple segments of the East Anatolian Fault system in Turkey. We integrate multi-scale seismic and space-geodetic observations with multi-fault kinematic inversions and dynamic rupture modeling to unravel the events’ complex rupture history and stress-mediated fault interactions. Our analysis reveals three sub-shear slip episodes during the initial M w 7.8 earthquake with delayed rupture initiation to the southwest. The M w 7.7 event occurred 9 hours later with larger slip and supershear rupture on its western branch. Mechanically consistent dynamic models accounting for fault interactions can explain the unexpected rupture paths, and require a heterogeneous background stress. Our results highlight the importance of combining near- and far-field observations with data-driven and physics-based models for seismic hazard assessment. 

Physics‐based simulations of earthquake ground motion are useful to complement recorded ground motions. However, the computational expense of performing numerical simulations hinders their applicability to tasks that require real‐time solutions or ensembles of solutions for different earthquake sources. To enable rapid physics‐based solutions, we present a reduced‐order modeling approach based on interpolated proper orthogonal decomposition (POD) to predict peak ground velocities (PGVs). As a demonstrator, we consider PGVs from regional 3D wave propagation simulations at the location of the 2008M_W5.4 Chino Hills earthquake using double‐couple sources with varying depth and focal mechanisms. These simulations resolve frequencies ≤1.0 Hz and include topography, viscoelastic attenuation, and S‐wave speeds ≥500 m/s. We evaluate the accuracy of the interpolated POD reduced‐order model (ROM) as a function of the approximation method. Comparing the radial basis function (RBF), multilayer perceptron neural network, random forest, andk‐nearest neighbor, we find that the RBF interpolation gives the lowest error (≈0.1 cm/s) when tested against an independent data set. We also find that evaluating the ROM is 10⁷–10⁸times faster than the wave propagation simulations. We use the ROM to generate PGV maps for 1 million different focal mechanisms, in which we identify potentially damaging ground motions and quantify correlations between focal mechanism, depth, and accuracy of the predicted PGV. Our results demonstrate that the ROM can rapidly and accurately approximate the PGV from wave propagation simulations with variable source properties, topography, and complex subsurface structure.

 

Abstract We measure pseudospectral and peak ground motions from 44 intermediate‐depth Mw≥4.9 earthquakes in the Cook Inlet region of southern Alaska, including those from the 2018 Mw 7.1 earthquake near Anchorage, to identify regional amplification features (0.1–5  s period). Ground‐motion residuals are computed with respect to an empirical ground‐motion model for intraslab subduction earthquakes, and we compute bias, between‐, and within‐event terms through a linear mixed‐effects regression. Between‐event residuals are analyzed to assess the relative source characteristics of the Cook Inlet earthquakes and suggest a difference in the scaling of the source with depth, relative to global observations. The within‐event residuals are analyzed to investigate regional amplification, and various spatial patterns manifest, including correlations of amplification with depth of the Cook Inlet basin and varying amplifications east and west of the center of the basin. Three earthquake clusters are analyzed separately and indicate spatial amplification patterns that depend on source location and exhibit variations in the depth scaling of long‐period basin amplification. The observations inform future seismic hazard modeling efforts in the Cook Inlet region. More broadly, they suggest a greater complexity of basin and regional amplification than is currently used in seismic hazard analyses.