An assessment of the tsunami risk in Muscat and Salalah, Oman, based on estimations of probable maximum loss. / Browning, John; Thomas, Neil.

In: International Journal of Disaster Risk Reduction, Vol. 16, 01.06.2016, p. 75-87.

Research output: Contribution to journalArticle

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Abstract

We present a method for determining an initial assessment of tsunami risk, with application for two coastal areas of Oman. Using open source GIS and seismic databases we carry out a tsunami risk assessment using a deterministic and probabilistic approach based on worst-case scenarios. A quick and effective method for estimating tsunami run-up without the use of complex modelling software is an important step in disaster risk reduction efforts as many government and emergency response organisations do not possess the expertise to carry out or interpret tsunami inundation numerical models. Estimates of probable maximum loss were calculated using a simple method of building identification and a revised building damage assessment technique. A series of tsunami risk maps were created for the coastal settlements of Muscat and Salalah, with the aim of improving tsunami response. We find Muscat to be at far greater risk of tsunami damage than Salalah; this is due in part to Muscat’s proximity to potential tsunamigenic sources and the cities current level of urban infrastructure. Whilst much of the infrastructure in Salalah is currently at low risk from tsunami, development pressures could lead to increased risk within the region. It is hoped that the assessment of risk may go some way to a government led disaster risk reduction strategy being implemented in coastal Oman. The methods detailed provide a cheap and efficient means to quantify tsunami risk in many coastal Middle Eastern countries, of which several have poor disaster risk reduction strategies.
Original languageEnglish
Pages (from-to)75-87
Number of pages14
JournalInternational Journal of Disaster Risk Reduction
Volume16
Early online date10 Feb 2016
DOIs
Publication statusPublished - 1 Jun 2016
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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