Earthquakes drive large-scale submarine canyon development and sediment supply to deep-ocean basins.

Although the global flux of sediment and carbon from land to the coastal ocean is well known, the volume of material that reaches the deep ocean-the ultimate sink-and the mechanisms by which it is transferred are poorly documented. Using a globally unique data set of repeat seafloor measurements and samples, we show that the moment magnitude (Mw) 7.8 November 2016 Kaikoura earthquake (New Zealand) triggered widespread landslides in a submarine canyon, causing a powerful "canyon flushing" event and turbidity current that traveled >680 km along one of the world's longest deep-sea channels. These observations provide the first quantification of seafloor landscape change and large-scale sediment transport associated with an earthquake-triggered full canyon flushing event. The calculated interevent time of ~140 years indicates a canyon incision rate of 40 mm year-1, substantially higher than that of most terrestrial rivers, while synchronously transferring large volumes of sediment [850 metric megatons (Mt)] and organic carbon (7 Mt) to the deep ocean. These observations demonstrate that earthquake-triggered canyon flushing is a primary driver of submarine canyon development and material transfer from active continental margins to the deep ocean.

Real-time forecasts of tomorrow's earthquakes in California.

Despite a lack of reliable deterministic earthquake precursors, seismologists have significant predictive information about earthquake activity from an increasingly accurate understanding of the clustering properties of earthquakes. In the past 15 years, time-dependent earthquake probabilities based on a generic short-term clustering model have been made publicly available in near-real time during major earthquake sequences. These forecasts describe the probability and number of events that are, on average, likely to occur following a mainshock of a given magnitude, but are not tailored to the particular sequence at hand and contain no information about the likely locations of the aftershocks. Our model builds upon the basic principles of this generic forecast model in two ways: it recasts the forecast in terms of the probability of strong ground shaking, and it combines an existing time-independent earthquake occurrence model based on fault data and historical earthquakes with increasingly complex models describing the local time-dependent earthquake clustering. The result is a time-dependent map showing the probability of strong shaking anywhere in California within the next 24 hours. The seismic hazard modelling approach we describe provides a better understanding of time-dependent earthquake hazard, and increases its usefulness for the public, emergency planners and the media.