Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/14641
Authors: Basili, Roberto* 
Brizuela, Beatriz* 
Herrero, André* 
Iqbal, Sarfraz* 
Lorito, Stefano* 
Maesano, Francesco Emanuele* 
Murphy, Shane* 
Perfetti, Paolo* 
Romano, Fabrizio* 
Scala, Antonio* 
Selva, Jacopo* 
Taroni, Matteo* 
Tiberti, Mara Monica* 
Thio, Hong-Kie* 
Tonini, Roberto* 
Volpe, Manuela* 
Glimsdal, Sylfest* 
Harbitz, Carl Bonnevie* 
Løvholt, Finn* 
Baptista, Maria Ana* 
Carrilho, Fernando* 
Matias, Luis Manuel* 
Omira, Rachid* 
Babeyko, Andrey* 
Hoechner, Andreas* 
Gurbuz, Mucahit* 
Pekcan, Onur* 
Yalciner, Ahmet* 
Canals, Miquel* 
Lastras, Galderic* 
Agalos, Apostolos* 
Papadopoulos, Gerassimos* 
Triantafyllou, Ioanna* 
Benchekroun, Sabah* 
Agrebi Jaouadi, Hedi* 
Ben Abdallah, Samir* 
Bouallegue, Atef* 
Hamdi, Hassene* 
Oueslati, Foued* 
Amato, Alessandro* 
Armigliato, Alberto* 
Behrens, Jörn* 
Davies, Gareth* 
Di Bucci, Daniela* 
Dolce, Mauro* 
Geist, Eric L.* 
González Vida, Manuel José* 
González, Mauricio* 
Macías Sánchez, Jorge* 
Meletti, Carlo* 
Ozer Sozdinler, Ceren* 
Pagani, Marco* 
Parsons, Tom* 
Polet, Jascha* 
Power, William* 
Sørensen, Mathilde B* 
Zaytsev, Andrey* 
Title: The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)
Other Titles: NEAM Tsunami Hazard Model 2018
Journal: Frontiers in Earth Science 
Series/Report no.: /8(2021)
Publisher: Frontiers
Issue Date: 5-Mar-2021
DOI: 10.3389/feart.2020.616594
Keywords: probabilistic tsunami hazard assessment
earthquake-generated tsunami
hazard uncertainty analysis
ensemble modeling
maximum inundation height
NEAM
Subject Classification05.08. Risk 
03.02. Hydrology 
04.06. Seismology 
04.07. Tectonophysics 
05.01. Computational geophysics 
Abstract: The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.
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