A heuristic features selection approach for scenario analysis in a regional seismic probabilistic tsunami hazard assessment. (August 2022)

• Record Type: Journal Article
• Authors: Di Maio, Francesco; Gallo, Nicola; Taroni, Matteo; Baglione, Enrico; Selva, Jacopo; Zio, Enrico
• Is Part Of: International journal of disaster risk reduction. Volume 78(2022)
• Publication Date: 2022-08
• Subjects: Seismic probabilistic tsunami hazard analysis (SPTHA) -- Scenario selection -- Feature selection -- Wrapper approach -- Multi-objective differential evolution algorithm (MODEA); Emergency management -- Periodicals; Risk management -- Periodicals; Disaster relief -- Periodicals; Hazard mitigation -- Periodicals; 363.34
• DOI: 10.1016/j.ijdrr.2022.103112
• Languages: English
• ISSNs: 2212-4209

Abstract

Abstract: Seismic Probabilistic Tsunami Hazard Analysis (SPTHA) is aimed at estimating the annual rate of exceedance of an earthquake-induced tsunami wave of a certain location with reference to a predefined height threshold. The analysis relies on computationally demanding numerical simulations of seismic-induced tsunami wave generation and propagation. A large number of scenarios needs to be simulated to account for uncertainties. However, the exceedance of tsunami wave threshold height is a rare event so that most of the simulated scenarios bring little statistical contribution to the estimation of the annual rate yet increasing the computational burden. To efficiently address this issue, we propose a wrapper-based heuristic approach to select the set of most relevant features of the seismic model, for deciding a priori the seismic scenarios to be simulated. The proposed approach is based on a Multi-Objective Differential Evolution Algorithm (MODEA) and is developed with reference to a case study whose objective is calculating the annual rate of threshold exceedance of the height of tsunami waves caused by subduction earthquakes that might be generated on a section of the Hellenic Arc, and propagated to a set of target sites: Siracusa, on the eastern coast of Sicily, Crotone, on the southern coast of Calabria, and Santa Maria di Leuca, on the southern coast of Puglia. The results show that, in all cases, the proposed approach allows a reduction of 95% of the number of scenarios with half of the features to be considered, and with no appreciable loss of accuracy.