Developing geospatial algorithms for fault identification along the Cascadia Subduction Zone

Abstract:

Many primary fault zones that host large earthquakes, such as the subduction zone megathrust in Cascadia, occur in offshore settings. The tectonic geomorphology of the seafloor above these offshore fault systems has been historically difficult to study due to limitations in observational techniques. Observations of fault-related offshore surface deformation within the forearc at subduction zones can be indicative of high-magnitude or recent geologic deformation and can give insight into tectonic stress regimes and associated faulting hazards. We created an algorithm that uses geospatial analytical tools to identify seafloor faulting structures from multibeam bathymetric data. We utilize newly acquired high resolution (20m) multibeam bathymetric data covering the shelf, rise, and trench, as well as multibeam water column data, and high-resolution seismic reflection data collected across the Cascadia active margin. Geospatial analytical methods, consisting of the slope and aspect of surface morphology, are tuned for surface fault identification along this margin. Faults identified from a slope-aspect signature are confirmed through comparison to faults that appear to reach the seafloor in seismic reflection data. Disruption of the bottom-simulating reflector (BSR) at faults that reach the surface is also used as an indicator of possible localization of methane gas along recently-active fault structures. This algorithm enhances our capabilities to accurately identify surface deforming faults in bathymetric datasets, which improves our ability to characterize deformation patterns and seismic hazards along the Cascadia active margin. Further applications of the slope-aspect algorithm could provide an additional perspective on the spatial distribution of surface deformation in subduction zone environments, thus contributing to our understanding of global tectonic processes and earthquake hazards near population centers like those in Cascadia.