Fingerprinting Subduction Margins: An Unsupervised Learning Approach for Earthquake Hazard Assessment

All observed giant (≥ M_W 8.5) earthquakes have occurred at subduction margins. Due to their long intermittence times, our instrumental and historical earthquake catalogues only contain a handful of giant earthquake occurrences, with no observations at all for some margins. This raises the question whether giant earthquakes may occur at all subduction margins or whether their nucleation requires a certain set of geological properties, which may be present at only some margins.

Since the 1980s, numerous studies have focused on the search for a subduction margin property enabling giant earthquakes, with parameters such as sediment thickness, subducting plate age and hydration, seafloor roughness, convergence rate, and dip steepness amongst the most debated, many of them with contradicting hypotheses. Recent years have brought the hypothesis that giant earthquake occurrence may depend on a combination of margin properties to the forefront, with several studies taking multivariate statistics approaches to relating the two. These approaches are however limited by the incomplete nature of earthquake catalogues, specifically regarding giant earthquakes.

We present an unsupervised approach to examining the connections between margin properties and seismicity, which allows us to uncover patterns in margin property data, excluding any earthquake occurrence data from the incomplete record. Considering sediment thickness, convergence rate, dip angle, and different measures of seafloor roughness, we “fingerprint” margin segments by applying Principal Component Analysis (PCA) to margin property data. Based on these “fingerprints”, we quantify similarity between the margins’ property combinations, and group them into different hazard groups regarding the possibility of giant earthquake occurrence. Using Kernel-PCA, a non-linear PCA variant, reveals non-linear patterns in margin properties, prompting us to suggest that connections between margin properties and seismicity are non-linear. Finally, we apply this method to characterise the seismic behaviour of subduction zones where seismic activity is less well-documented, such as the Makran, Hellenic, and Lesser Antilles margins.