PEER has just published Report No. 2016/03 titled “Simulation Confidence in Tsunami-Driven Overland Flow.” It was authored by Patrick Lynett.
Numerical models are a key component for methodologies used to estimate tsunami risk, and model predictions are essential for the development of Tsunami Hazard Assessments (THAs). By better understanding model bias and uncertainties and, if possible, minimizing them, a more reliable THA will result. This study compares the run-up height, inundation lines, and flowvelocity field measurements between GeoClaw and the Method of Splitting Tsunami (MOST) model predictions in the Sendai Plain. In general, run-up elevation and average inundation distance are overpredicted by the models. However, both models agree relatively well with each other when predicting maximum sea surface elevation and maximum flow velocities. To explore the variability and uncertainties in the numerical models, the MOST model is used to compare predictions from four different grid resolutions (30 m, 20 m, 15 m, and 10m). Our work shows that predictions of statistically stable products (run-up, inundation lines, and flow velocities) do not require use of high-resolution (less than 30 m) Digital Elevation Maps (DEMs) at this particular location. In addition, the Froude number variation in overland flow is presented. The results provided in this paper will help understand the uncertainties in model predictions and
locate possible sources of errors within a model.