Abstract

The seismogenic characteristics of the Gulf of Aqaba zone have been assessed using the maximum likelihood method to estimate various earthquake recurrence parameters. These parameters encompass the β-value, annual recurrence rate (λ), and maximum probable magnitude (Mmax). This assessment has identified three sub-seismogenic zones, each corresponding to specific structural faults within the Gulf. These zones are associated with the Aragonese, Arnona and Aqaba faults, delineating pull-apart basin structures in the Gulf of Aqaba. An updated earthquake catalogue has been compiled using a unified moment magnitude (Mw) scale to improve the analysis, established by developing two empirical relationships. According to the findings of this study, there is a possibility that the Aragonese seismogenic zone could experience an earthquake with a maximum magnitude of 7.7, highlighting a significant seismic hazard in the region. While acknowledging the inherent uncertainties in this assessment, a probabilistic seismic hazard was calculated for hard rock conditions within a spatial area divided into elementary cells, each measuring 0.1°x0.1°. The highest peak ground acceleration (PGA) is associated with a spectral frequency of 5.0 to 10.0 Hz and could significantly impact building codes in the region. The spatial distribution variations of seismic hazard corresponding to the proposed sub-seismogenic zones indicate a high degree of crustal heterogeneity and seismotectonic complexity. This comprehensive assessment contributes to understanding seismic hazards that may import from the Gulf of Aqaba seismogenic zone.

Department(s)

Geosciences and Geological and Petroleum Engineering

Publication Status

Open Access

Comments

King Saud University, Grant None

Keywords and Phrases

Earthquake recurrence characteristics; Gulf of Aqaba; Seismic hazard; Seismicity

International Standard Serial Number (ISSN)

1018-3647

Document Type

Article - Journal

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2024 Elsevier; King Saud University, All rights reserved.

Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Date

01 Apr 2024

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