GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 248-2
Presentation Time: 1:50 PM

2D AND 3D MODELING OF TSUNAMI INUNDATION: A CASE STUDY OF SEASIDE, OREGON


QIN, Xinsheng1, MOTLEY, Michael1, LEVEQUE, Randall J.2 and GONZALEZ, Frank I.3, (1)Civil and Environmental Engineering, University of Washington, Seattle, WA 98105, (2)Department of Applied Mathematics, University of Washington, Box 353925, Seattle, 98195-3925, (3)Department of Earth and Space Sciences, University of Washington, Box 351310, Seattle, WA 98195-1310, xsqin@uw.edu

Numerical modeling of tsunami inundation can provide very useful information for tsunami hazard mitigation. Traditionally, depth-averaged 2D models are used, which assumes independence of z coordinate (in the vertical direction). Although such approaches need much less computational resources compared to 3D models, they: 1) can be oversimplified to model the details of the complex and variable flow in the vertical direction; 2) can not model the the constructed environment onshore directly but only incorporate them as topography. The 3D models can incorporate geometry information of the constructed environment directly into the model, producing high-resolution results around coastal structures but requires very fine mesh near the constructed environment, which dramatically increases the computational cost and makes modeling of some problems impractical. In this study, we modeled tsunami inundation in Seaside, Oregon with both a 2D Nonlinear Shallow Water Equation model and a 3D Reynolds Averaged Navier-Stokes model. Required computational resources, accuracy of the results (inundation depth, flow velocities, tsunami impact forces etc.) and capability of the two models are compared and discussed. Several conclusions are made, including: 1) Modeling reasonably selected subdomains alleviates the computational cost of the otherwise impractical 3D model; 2) the 2D model does not accurately capture the important details of the flow near initial impact due to the transiency and large vertical variation of the flow, while the 3D model does a better job at a much higher cost of computational resources; 3) The 3D model can predict tsunami load by integrating predicted pressure on structural surfaces while the 2D model can do this from the momentum flux, which, however, is showed to be unreliable in complicated cases.