Abundant Spontaneous and Dynamically Triggered Submarine Landslides in the Gulf of Mexico

Submarine landslides that occur offshore are common along the U.S. continental margins. These mass wasting events can trigger tsunamis and hence potentially devastate coastal communities and damage offshore infrastructure. However, the initiation and failure processes of submarine landslides are poorly understood. Here, we identify and locate 85 previously unknown submarine landslides in the Gulf of Mexico from 2008 to 2015. Ten of these landslides failed spontaneously while the remaining 75 were dynamically triggered by passing seismic surface waves from distant earthquakes with magnitudes as small as similar to 5. Our observations demonstrate ongoing submarine landslide activity in the Gulf of Mexico where dense energy industry infrastructure is present and that the region is prone to secondary seismic hazard despite the low local seismicity rate. Our results should facilitate future investigations to identify unstable offshore slopes, to illuminate dynamic processes of landslides, and perhaps to apply remote detection technology in tsunami warning systems. Plain Language Summary Landslides under the ocean are termed submarine landslides. Submarine landslides can pose hazards to coastal communities and offshore infrastructure, including triggering tsunamis and damaging oil platforms, pipelines, and submarine cables. These devastations may further cause environmental damages such as oil spills. Identifying these landslides and understanding their failure processes have both societal significance and intellectual merit. Using 8 years of continuous seismic data, we found 85 previously unknown submarine landslides in the Gulf of Mexico from 2008 to 2015. Ten of these landslides occurred without preceding earthquakes while the remaining 75 were triggered by the passing seismic surface waves from distant earthquakes. Our approach suggests that a remote detection technology for offshore landslides could be applied in tsunami warning systems.