Resolving tsunami wave dynamics: Integrating sedimentology and numerical modelling

Abstract

Abstract Tsunamis are a major hazard along many of the world's coastlines. To understand the impact of these events, a sufficiently long record of previous events is needed, which can be provided by their sedimentary deposits. A number of past events have left extensive sedimentary deposits that can be used to understand the hydrodynamics of the tsunami. The ca 8.15 ka Storegga submarine slide was a large, tsunamigenic mass movement off the coast of Norway. The resulting tsunami had estimated run‐up heights of around 10 to 20 m on the Norwegian coast, over 30 m in Shetland and 3 to 6 m on the Scottish mainland coast. New cores were taken from the Ythan Valley in North‐East Scotland, where Storegga tsunami deposits have previously been found. High‐resolution sedimentary analyses of the cores, combined with statistical (changepoint) analysis, shows signatures of multiple waves. Moreover, detailed CT scans of the erosional basal surface reveal sole marks called skim marks. Taken in conjunction with the grain size and sedimentary fabric characteristics of the tsunami deposits, this indicates that the flow exhibited a high‐concentration basal component, with an initial semi‐cohesive phase and that deposition was dominantly capacity driven. A multiple wave hypothesis is tested by creating a high‐resolution numerical model (metre‐scale) of the wave inundation, coupled to a previously published regional model. The inundation model confirms that multiple waves passed over the site in agreement with the sedimentological analysis. The sensitivity of the model to the reconstructed palaeocoastal geomorphology is quantitatively explored. It is concluded that local palaeogeomorphological reconstruction is key to understanding the hydrodynamics of a tsunami wave group in relation to its sedimentary deposit. Combining sedimentological data with high‐resolution inundation modelling is a powerful tool to help interpret the sedimentary record of tsunami events and hence to improve knowledge of their risks.

Keywords

• modelling
• sedimentary analysis
• Storegga
• tsunami