Probabilistic Smf Tsunami Hazard Assessment For The Upper East Coast Of The United States

Abstract

The level of tsunami hazard to the east coast of the United States is not well understood. This information is critical for the population, emergency services, and industry of the region. Assessing this hazard is particularly difficult because of the lack of tsunamis in the historical record and the uncertainty regarding the return periods of large-scale events that have been proposed, such as a large transoceanic tsunami possibly caused by a collapse of the Cumbre Vieja volcano in the Canary Islands, or a large coseismic tsunami initiated in the Puerto Rican subduction zone. The most significant tsunami hazard in this region, however, may be due to local submarine mass failures (SMF), which could cause concentrated damage in coastal communities located near the failures. This paper presents results of a probabilistic analysis that estimates the hazard, expressed in terms of runup (at a given probability of occurrence), of SMF tsunamis triggered by earthquakes, on the upper northeast coast of the United States. A Monte Carlo approach is employed, in which distributions of relevant parameters (seismicity, sediment properties, type and location of slide, volume of slide, water depth, etc.) are used to perform large numbers of stochastic stability analyses of underwater slopes, based on standard geotechnical methods. When slope failure occurs, initial tsunami characteristic height and runup are estimated, based on earlier numerical work, for specified return periods of seismic events. The overall hazard associated with SMF tsunamis along the coast is found to be quite low at most locations as compared, e.g., to the typical 100 year hurricane storm surge in the region (5 m). Two sites, however, located off of Long Island, New York and Atlantic City, New Jersey, show an elevated risk of higher tsunami runup (5.0-7.5 m). These two sites should be the focus of more detailed studies.

Probabilistic assessment of landslide tsunami hazard for the northern Gulf of Mexico

“…Therefore, as a first-order estimate of tsunamigenic potential, a Monte Carlo Simulation (MCS) methodology is implemented to determine trial SMF scenarios and calculate the probability of failure and tsunami generation. Previous studies by Maretzki et al [2007] and Grilli et al [2009] used a similar MCS approach to assess landslide tsunami hazard along the east coast of the United States, and work by Shigihara and Horrillo [2014] applied the techniques of Maretzki et al [2007] and Grilli et al [2009] to the unique bathymetry of the GoM. However, while those studies determined potential slope failure based on independent distributions of parameters for landslide location and geometry, strong correlations between certain size parameters are evident based on previous GoM SMF events, specifically the values for area, volume, and length.…”

“…The MCS methodology discussed here to determine SMF sources expands on that presented in Maretzki et al . [], Grilli et al . [], and Shigihara and Horrillo [], and a summary of the procedure is as follows.…”

“…Previous studies by Maretzki et al . [] and Grilli et al . [] used a similar MCS approach to assess landslide tsunami hazard along the east coast of the United States, and work by Shigihara and Horrillo [] applied the techniques of Maretzki et al .…”

“…[] used a similar MCS approach to assess landslide tsunami hazard along the east coast of the United States, and work by Shigihara and Horrillo [] applied the techniques of Maretzki et al . [] and Grilli et al . [] to the unique bathymetry of the GoM.…”

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

“…Determining rates of occurrence tends to be more problematic for nonearthquake sources compared with earthquake sources because they often lack any clear time dependence, and source mechanisms can be strongly nonlinear. Probabilistic hazard assessments of tsunamis from submarine mass failures, some including the potential for earthquake triggering, have been undertaken for the U.S. Atlantic (Geist & Parsons, 2010;Grilli et al, 2009;Lynett & Martinez, 2012;Maretzki et al, 2007;ten Brink et al, 2009ten Brink et al, , 2014 and Pacific margins (Watts, 2004), the Canadian coast (Leonard et al, 2014), New Zealand coasts (Lane, Mountjoy, Power, & Mueller, 2016), and the Tyrrhenian Sea (e.g., Grezio et al, 2012Grezio et al, , 2015. Probabilistic analysis of meteotsunamis were introduced by and Šepić, Medugorac, et al (2016) for the northeast U.S. coastlines and the Balearic Islands, Spain, respectively.…”