NH12A-05:
Assessment of Landslide-Tsunami Hazard for the Gulf of Mexico Using a Probabilistic Approach

Monday, 15 December 2014: 11:20 AM
Alyssa Pampell1, Juan J Horrillo1, Lisha Parambath1 and Yoshinori Shigihara2, (1)Texas A & M University at Galveston, Galveston, TX, United States, (2)National Defense Academy, Civil and Environmental Engineering, Yokosuka, Japan
Abstract:
The devastating consequences of recent tsunami events in Indonesia (2004) and Japan (2011) have prompted a scientific response in assessing tsunami hazard even in regions where an apparent low risk or/and lack of complete historical tsunami record exists. Although a great uncertainty exists regarding the recurrence rate of large-scale tsunami events in the Gulf of Mexico (GOM) due to sparsity of data, geological and historical evidences indicate that the most likely tsunami hazard could come from a submarine landslide triggered by a moderate earthquake. Under these circumstances, the assessment of the tsunami hazard in the region could be better accomplished by means of a probabilistic approach to identify tsunami sources.

This study aims to customize for the GOM a probabilistic hazard assessment based on recurrence rates of tsunamigenic submarine mass failures (SMFs). The Monte Carlo Simulation (MCS) technique is employed utilizing matrix correlations for landslide parameters to incorporate the uncertainty related to location/water-depth and landslide dimension based on lognormal/normal distributions obtained from observed data. Along fixed transects over the continental slope of the GOM, slide angle of failure, sediment properties and seismic peak horizontal accelerations (PHA) are determined by publicly available data. These parameter values are used to perform slope stability analyses in randomly generated translational SMFs obtained from the MCS technique. Once the SMF is identified as tsunamigenic for a given PHA recurrence rate, a preliminary tsunami amplitude can be estimated using empirical formulations. Thus, the annual probability of a tsunamigenic SMF is determined by the joint probability of failure with the annual PHA.

By using the probabilistic approach, we identified tsunami sources with recurrence rates from few thousands to 10,000 years which produce extreme wave amplitudes for each transect. The most likely extreme tsunamigenic SMF events for a given transect are then modeled to determine hazard to specific coastal locations, including maximum runup heights, inundation depth/extent, and strong currents affecting communities and infrastructure, thus mitigating the impact of tsunamis according to the guidelines of the National Tsunami Hazard Mitigation Program.