S21B-4441:
Size Distribution of Slip Values in Finite-Fault Rupture Models
Tuesday, 16 December 2014
Kiran Kumar Singh Thingbaijam and Paul Martin Mai, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Abstract:
Understanding statistical properties of earthquake sources is crucial for proper ground-motion predictions. We investigate the size distribution of slip values as imaged by finite-fault rupture models. Our analysis utilizes rupture models from the SRCMOD database (
http://equake-rc.info/srcmod). To overcome the limitation of variable spatial sampling across different models, we consider combined areas of fault-rupture corresponding to different slip bins. The slip values in each rupture model are binned according to fractions of the overall maximum slip. We refer to the rupture area occupied by a specified slip bin as slip-area. To eliminate possible spurious small slip at the fault edge, we compute the effective source dimensions from the slip distribution, accounting for sub-fault size, location of slip-asperities, and surface rupture (if present). This procedure includes trimming the model to the smallest dimensions that accommodate the autocorrelation width of the slip distribution (Mai and Beroza, 2000). We modify the trimming process to not affect any large slip asperity (
u ≥
umax/3) where
u and
umax denote slip and maximum slip value. In order to look beyond individual models, we develop scaling relationships between seismic moment and slip-areas. These relationships are, thereafter, employed to derive average tail distribution (or exceedance) of the slip values. Our regression analysis reveals that self-similar source scaling holds for dip-slip events while scale invariance breaks down for large strike-slip events. We find that the tail distributions of the slip values can be described by stretched-exponential functions, with the averaged distribution close to exponential. This characterization of the slip distribution agrees with the source scaling laws, and will be useful in generating realistic earthquake rupture scenarios for ground-motion modeling.