AUTHOR=Schäfer Andreas M. , Wenzel Friedemann TITLE=Global Megathrust Earthquake Hazard—Maximum Magnitude Assessment Using Multi-Variate Machine Learning JOURNAL=Frontiers in Earth Science VOLUME=7 YEAR=2019 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2019.00136 DOI=10.3389/feart.2019.00136 ISSN=2296-6463 ABSTRACT=
Megathrust subduction faults have caused the largest earthquakes ever recorded in human history. In addition, they are often associated with devastating tsunamis. Thus, assessing their potential maximum magnitude and respective return periods is vital for seismic-tsunami hazard assessment. However, empirical data are limited, owing to their very-long recurrence period that can be several centuries or millennia. To bridge this gap of empirical data with seismotectonic observations, a combined assessment of maximum magnitudes and return periods was undertaken applying a variety of machine learning and conventional methods. For this purpose, 76 subduction zone segments have been assessed worldwide. This includes a 3D modeling of subduction slab geometries on the basis of earthquake hypocenters and a collection of various relevant parameters e.g., those of local geology, geodesy or seismicity. These parameters have been used to assess the potential maximum magnitudes using machine learning classification and other statistical methods. The results have been combined with a tapered Gutenberg-Richter seismicity model and plate tectonic modeling to quantify earthquake return periods and their uncertainties. They show that almost all major subduction zones have the potential to produce earthquakes