Can small islands protect nearby coasts from tsunamis? An active experimental design approach

Abstract

Small islands in the vicinity of the mainland are widely believed to offer protection from wind and waves and thus coastal communities have been developed in mainland areas behind small islands. However, whether they offer protection from tsunamis is unclear. Do islands act as natural barriers? Recent post-tsunami survey data, supported by numerical simulations, reveal that the run-up on coastal areas behind small islands was significantly higher than on neighbouring locations not affected by the presence of the islands. To study the conditions of this run-up amplification, we solve numerically the nonlinear shallow water equations. We use the simplified geometry of a conical island sitting on a flat seafloor in front of a uniform sloping beach. By doing so, the experimental set-up is defined by five physical parameters, namely the island slope, the beach slope, the water depth, the distance between the island and the plane beach and the incoming wavelength, while the wave height was kept fixed. The objective is to find the maximum run-up amplification with the least number of simulations. To achieve this goal, we build an emulator based on Gaussian Processes to guide the selection of the query points in the parameter space. We thus reduce substantially the computations required to identify the run-up amplification. Our results show that the island acts as a focusing lens for energy and amplifies the run-up along the coastline behind its lee side, instead of protecting it, as popular beliefs suggest.

Tsunamis: bridging science, engineering and society

“…To achieve their goal, Stefanakis et al [110] built an emulator based on Gaussian processes to guide the selection in the parameter space, thus reducing substantially the computations required to identify the run-up amplification; instead of 100 000, they found the maximum with about 200 simulations. Their results show that the island acts as a focusing lens for energy, and amplifies the run-up along the continental coastline behind its lee side, instead of protecting it, as popular beliefs suggest.…”

“…To test the hypothesis whether the run-up on coastal areas behind small islands was significantly higher than on neighbouring locations not affected by the presence of the islands. Stefanakis et al [110] used active learning to vary parameters in the simplified geometry of a conical island sitting on a flat seafloor in front of a uniform sloping beach. Their experiment was defined by five physical parameters, namely the island slope, the beach slope, the water depth, the distance between the island and the plane beach, and the incoming wavelength, while the wave height was kept fixed.…”

The hydrodynamics of landslide tsunamis: current analytical models and future research directions

“…Concerning the propagation of tsunamis around islands, recently Stefanakis et al (2014) have shown that focussing effects of incident waves around circular islands can lead to unexpected large runup behind the lee side, instead of protecting it. The hydrodynamic problem of tsunami generation in a circular geometry has been also considered by Stefanakis et al (2015), who analysed the generation of waves by an uplifting circular sill.…”

“…Indeed, modelling landslide tsunamis is intrinsically challenging as it involves a time-dependent bottom deformation in the same region where the waves are generated and propagate. In this paper, we shall review the analytical models of Sammarco and Renzi (2008), Renzi and Sammarco (2010) and Renzi and Sammarco (2012), which have become benchmark models for numerical codes (Romano et al 2013;Dias et al 2014;Stefanakis et al 2014) and statistical emulations (Sarri et al 2012) of landslide tsunamis. Analytical models provide an invaluable tool in the science of tsunami modelling, for they allow one to obtain a sound physical understanding of the wave dynamics and to carry out parametric investigations on the influence of the system main parameters on the maximum wave runup.…”

Prediction and optimization of wave energy converter arrays using a machine learning approach

“…This algorithm proceeds in an iterative way so as to reduce the uncertainty of the prediction of the best configuration. It has recently been used in the estimation of maximum wave run-up of tsunami waves behind conical islands [18]. At iteration t after having computed b m t and b s 2 t , we simultaneously explore the configurations with high uncertainty and focus on the ones with high prediction.…”