Estimation of submarine mass failure probability from a sequence of deposits with age dates

Abstract

The empirical probability of submarine mass failure is quantifi ed from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the fi rst and after the last event. The likelihood techniques are evaluated using Akaike's Information Criterion (AIC) and Akaike's Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio-and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasi peri odically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.

A probabilistic approach for landslide hazard analysis

“…Direct approaches are based on the analysis of available historical data of past landslides, which can also be related to geology, geomorphology, and other factors (Moon et al, 1992;Cruden, 1997;Jaiswal et al, 2011;Geist et al, 2013). Indirect approaches derive the landslide frequency from triggering factors, such as rainfall intensity and duration (Sidle et al, 1985;Crozier, 1997;Dai and Lee, 2001;Schuster and Wieczorek, 2002;D'Odorico et al, 2005;Rosso et al, 2006;Salciarini et al, 2008;Frattini et al, 2009), or earthquake (Del Gaudio et al, 2003Rathje and Saygili, 2008).…”

Submarine Mass Movements and their Consequences

“…Geist et al (2013) provide excellent methodologies for how errors and uncertainties in dating can further be addressed by statistical analysis. The sampled time windows range from 0.15 to 19.45 Ma and feature up to 1571 recurrence intervals.…”

“…This is largely due to uncertainties in dating individual landslides (Urlaub et al 2013), lack of sediment for dating (Geist et al 2013) and insufficiently large sample sizes for robust analysis (Urlaub et al 2013;. Determining the past frequency distribution of large slides is therefore important and can inform our estimates of future hazard rate (i.e.…”

“…Notable developments in quantifying slide probability include techniques used in palaeoseismology (Geist and Parsons 2009;Geist et al 2013). These novel studies present robust approaches accounting for different frequency distributions and address uncertainties using Bayesian and Monte Carlo methods for sub-optimal sample sizes (N < 14).…”

Source Processes for the Probabilistic Assessment of Tsunami Hazards

“…In addition to the challenge of including landslide sources, as well as volcanic sources (Paris et al, 2014) records is in assessing both the age and the size of prehistoric tsunami sources and quantifying the uncertainty in both of these parameters (Geist et al, 2013).…”