HR: 1340h
AN: OS23D-1346    [Abstracts]
TI: Estimation of Tsunami Hazard for the East Coast of Kamchatka Using Paleotsunami Runup
AU: Kaistrenko, V
EM: tsunami@sakhmail.ru
AF: Inst. Marine Geology & Geophysics FED RAS, Nauki St., Yuzhno-Sakhalinsk, 693022 Russian Federation
AU: Pinegina, T
EM: pinegtk@kcs.iks.ru
AF: Inst. of Volcanology & Seismology FED RAS, Piip Blvd. 9, Petropavlovsk-Kamcha, 683006 Russian Federation
AU: * Bourgeois, J
EM: jbourgeo@u.washington.edu
AF: Dept. Earth & Space Sciences, University of Washington, Seattle, WA 98195-1310 United States
AB: During the last 10 years, at more than 15 localities along about 700 km of the east coast of Kamchatka, we have investigated historical and paleotsunami deposits of more than 100 strong tsunamis (runup more than 5 m). Most localities provide a record 3000 to 5000 years long; with age control set primarily by well-mapped and dated tephra. Tsunami frequency has been calculated for at least the last 3000 years, with typical recurrence intervals of 50-200 years. For the biggest recorded events maximum wave height is estimated, as well as inundation (penetration) distance. We illustrate here that it is importent to use these new data about paleotsunami runup for tsunami hazard estimation. On Kamchatka we have done this for the first time for part of the Pacific coast (Khalaktyrka) near Petropavlovsk-Kamchatskiy, Kamchatka's population center. The quality of the model used for tsunami risk estimation depends on the dispersion of model parameters, tsunami frequency f and characteristic tsunami height H*. Accordingly, this dispersion depends on quality and quantity of natural data used for creation of the probability model. Three models using different tsunami data sets were considered. The first model was a homogeneous model based on the 50-year data set; the second model used the same set with an additional 15-meter run-up on the Khalaktyrka coast caused by the 1841 tsunami; and the third model used additional paleotsunami data for Khalaktyrka. Comparison among the models allows us to conclude that using paleotsunami data for an elected point combined with the historical data makes dispersion of the tsunami parameters f and H* much less.
DE: 7221 Paleoseismology
DE: 7223 Seismic hazard assessment and prediction
DE: 6699 General or miscellaneous
DE: 4564 Tsunamis and storm surges
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting