Numerical characterisation and efficient prediction of landslide-tsunami propagation over a wide range of idealised bathymetries: Fid-Bau Portal

Numerical characterisation and efficient prediction of landslide-tsunami propagation over a wide range of idealised bathymetries

Ruffini, Gioele / Heller, Valentin / Briganti, Riccardo

Abstract

Abstract Landslide-tsunamis are generated by masses, such as landslides or icebergs, impacting into water bodies. Such tsunamis resulted in major catastrophes in the recent past. Generic research into landslide-tsunamis has widely been conducted in idealised water body geometries at uniform water depths. However, varying bathymetries can significantly alter landslide-tsunamis. This article investigates this effect in a 2D flume using selected idealised bathymetries to provide methods to predict the transformed wave characteristics downwave of each feature. The selected bathymetries are: (a) linear beach bathymetries, (b) submerged positive and negative Gaussian bathymetric features and (c) submerged positive and negative step bathymetries. The hydrodynamic model SWASH, based on the non-hydrostatic non-linear shallow water equations, was used to simulate 9 idealised landslide-tsunamis (1 approximate linear, 2 Stokes, 2 cnoidal and 4 solitary waves), for a total of 184 tests. The analysed parameters include the free water surface, wave height and amplitude. Shoaling in (a) is represented by either Green's law or the Boussinesq's adiabatic approximation up to wave breaking with an accuracy of $- 7 %$ to $+ 10 %$ for cnoidal and solitary waves, respectively. The results are then analysed with an (i) Artificial Neural Network and (ii) a regression analysis. (i) shows a smaller Mean Square Error (MSE) of 0.0027 than (ii) (MSE $= 0.024$ ) and good generalisation in predicting the transformed wave characteristics and, after defining the best dimensionless parameters, (ii) provides empirical equations to predict transformed waves. In addition, simulations were conducted in a 3D basin to investigate the combined effect of the bathymetry and geometry. The efficient use of the developed prediction methods is demonstrated with the 2014 Lake Askja landslide-tsunami where a good accuracy is achieved compared to available numerical simulations.

Highlights • The effect of the bathymetry on landslide-tsunamis is investigated with a numerical model. • Wave parameters (height and amplitude) transformation in a wide range of bathymetries and wave conditions is analysed. • Artificial Neural Networks (ANNs) and regression analysis are used to predict the transformed wave parameters. • The combined effect of the bathymetry and water body geometry are found to alter the wave height by up to 30.4%. • The developed methods are successfully applied to the 2014 Lake Askja case with the ANN resulting in the best agreement.