Preprints
https://doi.org/10.5194/nhess-2018-221
https://doi.org/10.5194/nhess-2018-221
24 Jul 2018
 | 24 Jul 2018
Status: this preprint was under review for the journal NHESS. A revision for further review has not been submitted.

Tsunami Hazard assessment and Scenarios Database for the Tsunami Warning System for the coast of Oman

Íñigo Aniel-Quiroga, José A. Álvarez-Gómez, Mauricio González, Jara Martínez Sánchez, Laura M. Parro, Ignacio Aguirre-Ayerbe, Felipe Fernández, Raúl Medina, and Sultan Al-Yahyai

Abstract. Advances in the understanding of tsunami impacts allow developing products to assess its consequences in tsunami-prone areas, as it is the case of the coast of the Sultanate of Oman. This paper presents the followed methodology and the obtained results for the assessment of the tsunami hazard of the coast of Oman and the development of the scenario database that feeds its Tsunami Warning System (TWS). Initially, a seismo-tectonic analysis of the area was carried out, focused on identifying the seismic areas whose earthquakes could generate tsunamis affecting the coast of Oman. A database of 3181 tsunamigenic sources was characterized by means of the parameters that define their focal mechanisms. This database includes scenarios with magnitudes Mw ranging from 6.5 to 9.25 within the study area, but it is especially focused on the Makran Subduction Zone (MSZ). The 3181 cases were numerically propagated to feed the database and to work as precomputed scenarios for the TWS: In case of tsunami, the results for the closest precomputed scenario (in location and magnitude) are shown. From the database, 7 worst-case scenarios were selected and computationally simulated at national and local scale, in 9 municipalities all along the coast of Oman, resulting in tsunami hazard maps containing relevant variables in the flooded area, such as the inundation water depth and the drag level (hazard degree for people instability).

Finally, in order to manage conveniently the results, an online tool, called Multi-Hazard Risk Assessment System (MHRAS), was developed. This tool is a viewer that contains an easy-to-use application, including the results of the tsunami hazard assessment and the tsunami scenario database, and the selection algorithm to choose the proper case among the precomputed ones. The results of this research are part of the National Multi-Hazard Early Warning System of Oman (NMHEWS).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Íñigo Aniel-Quiroga, José A. Álvarez-Gómez, Mauricio González, Jara Martínez Sánchez, Laura M. Parro, Ignacio Aguirre-Ayerbe, Felipe Fernández, Raúl Medina, and Sultan Al-Yahyai
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Íñigo Aniel-Quiroga, José A. Álvarez-Gómez, Mauricio González, Jara Martínez Sánchez, Laura M. Parro, Ignacio Aguirre-Ayerbe, Felipe Fernández, Raúl Medina, and Sultan Al-Yahyai
Íñigo Aniel-Quiroga, José A. Álvarez-Gómez, Mauricio González, Jara Martínez Sánchez, Laura M. Parro, Ignacio Aguirre-Ayerbe, Felipe Fernández, Raúl Medina, and Sultan Al-Yahyai

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Latest update: 26 May 2024
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Short summary
In this work, two of the main strategies to reduce tsunami risk on the coast of Oman are addressed. The tsunami hazard assessment (calculation of the potentially flooded area) and the elaboration of a database of tsunami events that is a fundamental part of the Oman Tsunami Warning System. The study included the characterization of the tsunamigenic sources affecting the study area and the numerical simulation of their generation, propagation and inundation.
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