Text S1. DEM Modeling

In our implementation of the discrete-element-method (DEM), we simulate an assemblage of discrete spherical particles that interact with each other according to elastic-frictional (Hertz-Mindlin) contact law. We introduce cohesion by adding a mechanical bond at interparticle contacts (Morgan, 2015). This property can allow us to simulate cohesive materials as may occur within the deeper accretionary prism. The more frontal region of a prism is approximated as non-cohesive, i.e., lacking interparticle bonds. The combination of pre-assigned interparticle contact parameters, in combination with the mechanical properties of the particles themselves, define the overall behavior of the particle assemblage. This study uses a version of DEM implemented in RICEBAL. Details about the method are provided in Morgan and Boettcher (1999), Guo and Morgan (2004; 2006), and Morgan (2015). Continuum approximations of the bulk properties and behavior of the numerical model are derived using the contact force distribution and displacement gradients. By averaging continuum properties over finite volumes, stress and strain fields can be calculated for the domain (Thornton and Barnes, 1986; Morgan and Boettcher, 1999; Morgan and McGovern, 2005b; a; Morgan, 2015).
Figure S1 shows the general model setup. The initial length of the simulated wedge is set to 200 km, comparable to the dimensions of the rupture areas in Chile Margin (Moreno et al. , 2010; Contreras-Reyes et al. , 2017). To best balance model run time and model resolution, the upper wedge is constructed of approximately 200,000 discrete particles with radii of 100, 120, 160 and 200 m. Particles are randomly generated within a two-dimensional box (400\(\times\)60 km) and allowed to settle under gravity.
The mechanical properties of the simulated system are defined by the assigned particle properties and interparticle friction coefficients (Table S3). Particles within the wedge, indicated by the black and blue layers in Figure S1, are free to translate, rotate and interact as the wedge evolves. The gray particles defining the basal sliding surface are fixed in space, their small radii (10 m) ensure a relatively smooth sliding surface, unimpeded by particle roughness.
The coefficients of internal and basal sliding friction are determined by the interparticle friction coefficients assigned between wedge particles (\(\mu_{\text{int}}^{\text{part}}\)) and wedge and basal particles (\(\mu_{\text{bas}}^{\text{part}}\)) respectively. The calibrated relationships between the interparticle and bulk friction coefficients are presented in a previous study (Wang and Morgan, 2019). The assigned internal friction coefficient within the outer wedge and basal friction coefficient beneath are further annotated as\(\mu_{int\_outer}^{\text{part}}\) and\(\mu_{bas\_outer}^{\text{part}}\), respectively. Similarly, the internal and basal friction coefficients for the inner wedge are written as \(\mu_{int\_inner}^{\text{part}}\) and\(\mu_{bas\_inner}^{\text{part}}\). We tested multiple combinations of internal and basal friction values to obtain first order fits to observed earthquake displacements along the Chile margin, and selected the following interparticle friction coefficient as initial friction conditions for our simulations: \(\mu_{int\_outer}^{\text{part}}\) =\(\mu_{int\_inner}^{\text{part}}\)= 0.100 (friction coefficients between wedge particles), which remains fixed throughout the simulation; initial \(\mu_{bas\_outer}^{\text{part}}\) =\(\mu_{bas\_inner}^{\text{part}}\) = 0.040 (friction coefficients between wedge and basal particles), which is comparable to the effective basal friction coefficient used by Wang and He (2008). Basal friction coefficients are subsequently varied during the simulations as described below and in the text.