A tsunami scenario determination methodology based on probabilistic tsunami hazard assessment is demonstrated. First, contributions of potential tsunami sources to the hazard curve, which is the relationship between tsunami height and the annual frequency of exceedance, are analyzed to identify scenarios that would generate a tsunami at the target coast in a target height range. By considering similarities in tsunami wave form and current direction, similar tsunami scenarios are grouped, and major tsunami scenarios can be determined.
Assessing the tsunami hazard of coastal industrial facilities requires the consideration of multiple scenarios with regard to tsunami arrivals and their potentially severe impacts on society and business continuity planning. Identifying the potential spatial and temporal distributions of inundation depth and velocity for such events can aid in these determinations.
Probable maximum tsunamis (PMT) are sometimes used for identifications of tsunami inundation depths (e.g., Grilli et al., 2015; JSCE, 2012; U.S.NRC, 2016). Based on historical tsunami data and field surveys, potential tsunami source mechanisms are identified. By considering uncertainties regarding future tsunami generations, many tsunami source models are prepared. Among the source models, that of PMT is selected such that the highest tsunami height in front of the site were predicted (JSCE, 2012). However, the frequency of PMT is unknown.
The probabilistic tsunami hazard assessment (PTHA) methodology is used to evaluate the scale and frequency of future tsunamis (e.g., Mori et al., 2017). The logic-tree approach often used for PTHA systematically considers both epistemic (lack of knowledge) and aleatory (random variability) uncertainties regarding future tsunami prediction (e.g., Geist and Parsons, 2006; Annaka et al., 2007; JSCE, 2016). The former are expressed by tree branches while the latter are expressed by probabilistic density functions for predicted tsunami heights. JSCE (2016) develops a PTHA methodology and shows examples of logic trees for various sea areas around Japan. The PTHA methodology proposed by JSCE (2016) was based on the probabilistic seismic hazard assessment (PSHA) approach proposed by Cornell (1968).