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An empirical solution for tsunami run-up on compound slopes Public Deposited

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https://ir.library.oregonstate.edu/concern/articles/sx61dr60g

This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Springer and can be found at:  http://www.springer.com/earth+sciences+and+geography/natural+hazards/journal/11069

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  • Deterministic numerical models for tsunami inundation provide the most accurate means for estimating tsunami run-up when the bathymetry/topography and water level time history at the seaward boundary are well known. However, it is often the case that there is uncertainty in both the bathymetry/topography and water level at the seaward boundary. For these reasons, empirical solutions for tsunami run-up may be preferred because the run-up can be computed quickly allowing a probabilistic estimate the tsunami run-up risk. In this paper, an empirical solution for tsunami run-up is developed based on an analytic solution and calibrated using a Boussinesq wave model for plane-sloped and compound-sloped cases, including the effects of bottom friction, wave breaking, and the slope of the inundated land area. The new relation is a function of the tsunami wave amplitude at a specific water depth (100 m) to provide clear guidance for practical application, and of two values of the surf-similarity parameter to account for a compound slope. The model comprises three equations for three regions: breaking, transition and non-breaking. The model predictions are compared with survey data from the 2011 Tohoku tsunami in Japan without recalibration. The new equation provides reasonable estimates of run-up height and is generally conservative.
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  • Park, H., Cox, D. T., & Petroff, C. M. (2015). An empirical solution for tsunami run-up on compound slopes. Natural Hazards, 76(3), 1727-1743. doi:10.1007/s11069-014-1568-7
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  • This research is based upon the work partially supported by the National Science Foundation under Grant No. 0830378 and Oregon Sea Grant under Award No. NB223X.
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