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# Numerical modeling of tsunamis and tsunami vulnerability analysis for Heraklion, Crete

#### Flouri Evaggelia, Dougalis, Vassilios A, Synolakis Kostas

Πλήρης Εγγραφή

 URI: http://purl.tuc.gr/dl/dias/0CB1BB7E-4F50-4795-B6EC-1318443ABB17 Έτος 2018 Τύπος Δημοσίευση σε Περιοδικό με Κριτές Άδεια Χρήσης Βιβλιογραφική Αναφορά E.T. Flouri, V.A. Dougalis and C.E. Synolakis, "Numerical modeling of tsunamis and tsunami vulnerability analysis for Heraklion, Crete," Math. Method Appl. Sci., vol. 41, no. 3, pp. 1068-1073, Feb. 2018. doi: 10.1002/mma.4134 https://doi.org/10.1002/mma.4134 Εμφανίζεται στις Συλλογές Δημοσιεύσεις σε Περιοδικά στην Κοινότητα Σχολή Μηχανικών Περιβάλλοντος

## Περίληψη

Tsunamis are rare events compared with other extreme natural hazards, but the growth of population along coastlines has increased their potential impact. Tsunamis are most often generated by earthquake-induced dislocations of the seafloor, which displace large water masses. They can be simulated effectively as long waves whose propagation is modeled by the nonlinear shallow water equations. In this note, we present a brief assessment of earthquake-generated tsunami hazards for the city of Heraklion, Crete. We employ numerical hydrodynamic simulations, including inundation computations with the model MOST, and use high-resolution bathymetry and topography data for the area of interest. MOST implements a splitting method in space to reduce the system of shallow water equations in two successive systems, one for each spatial variable, and it uses a dispersive, Godunov-type finite difference method to solve the equations in characteristic form. We perform probabilistic analysis to assess the effects of the earthquake epicenter location on the tsunami, for time windows of 100, 500, and 1000years. The tsunami hazard is assessed through computed values of the maximum inundation range and maximum flow depth. Finally, we present a brief vulnerability analysis for the city of Heraklion, Crete. The data needed to identify tsunami-vulnerable areas are obtained by combining remote sensing techniques and geographic information system technology with surveyed observations and estimates of population data.