caa a22 4500 467936420 CHVBK 20180406152958.0 cr unu---uuuuu 170328e20060301xx s 000 0 eng 10.1007/s11069-005-4646-z doi (NATIONALLICENCE)springer-10.1007/s11069-005-4646-z Probabilistic Analysis of Tsunami Hazards* [Elektronische Daten] [Eric Geist, Tom Parsons] Determining the likelihood of a disaster is a key component of any comprehensive hazard assessment. This is particularly true for tsunamis, even though most tsunami hazard assessments have in the past relied on scenario or deterministic type models. We discuss probabilistic tsunami hazard analysis (PTHA) from the standpoint of integrating computational methods with empirical analysis of past tsunami runup. PTHA is derived from probabilistic seismic hazard analysis (PSHA), with the main difference being that PTHA must account for far-field sources. The computational methods rely on numerical tsunami propagation models rather than empirical attenuation relationships as in PSHA in determining ground motions. Because a number of source parameters affect local tsunami runup height, PTHA can become complex and computationally intensive. Empirical analysis can function in one of two ways, depending on the length and completeness of the tsunami catalog. For site-specific studies where there is sufficient tsunami runup data available, hazard curves can primarily be derived from empirical analysis, with computational methods used to highlight deficiencies in the tsunami catalog. For region-wide analyses and sites where there are little to no tsunami data, a computationally based method such as Monte Carlo simulation is the primary method to establish tsunami hazards. Two case studies that describe how computational and empirical methods can be integrated are presented for Acapulco, Mexico (site-specific) and the U.S. Pacific Northwest coastline (region-wide analysis). Springer, 2006 tsunami nationallicence probabilistic hazard analysis nationallicence seismic hazard analysis nationallicence Monte Carlo nationallicence tide gauge nationallicence empirical nationallicence power-law nationallicence Geist Eric U.S. Geological Survey, 345 Middlefield Rd., MS 999, 94025, Menlo Park, CA, USA aut Parsons Tom U.S. Geological Survey, 345 Middlefield Rd., MS 999, 94025, Menlo Park, CA, USA aut Natural Hazards Kluwer Academic Publishers 37/3(2006-03-01), 277-314 0921-030X 37:3<277 2006 37 11069 https://doi.org/10.1007/s11069-005-4646-z text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11069-005-4646-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Geist Eric U.S. Geological Survey, 345 Middlefield Rd., MS 999, 94025, Menlo Park, CA, USA aut NATIONALLICENCE 700 1- Parsons Tom U.S. Geological Survey, 345 Middlefield Rd., MS 999, 94025, Menlo Park, CA, USA aut NATIONALLICENCE 773 0- Natural Hazards Kluwer Academic Publishers 37/3(2006-03-01), 277-314 0921-030X 37:3<277 2006 37 11069 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer