H. Zahran, V. Sokolov, S. El-Hadidy Youssef, W. W. Alraddadi, M. J. Roobol, I. C. F. Stewart, M. El-Hadidy
For any additional information about this model please contact: Zahran.HM@sgs.org.sa
The 2018 seismic hazard model of the Arabian Peninsula (ARB) was developed by the Saudi Geological Survey (SGS). The model covers Saudi Arabia, Yemen, Oman, and Qatar. The model has been translated into the OpenQuake (OQ) engine format by GEM.
Information about the OQ model versions and input files can be found on the Results and Dissemination page.
The viewer below depicts the seismic sources and hazard results in terms of PGA for a return period of 475 years. Click on the menu in the upper right corner to select the layer.
The Arabian Peninsula is a microcontinent on its own tectonic plate in between southern Eurasia and Africa. The plate moves northward relative Eurasia at ~20 mm/yr, resulting in continental convergence and thrust faulting within the Zagros and eastern Anatolian fold belts to the north (which to the southeast continues as subduction of oceanic crust under Iran and western Pakistan), and left-lateral strike-slip faulting along the Dead Sea Transform in the east. To the south, Arabia is moving away from northeastern Africa, leading to oceanic spreading centers in the Red Sea and Gulf of Aden; these form two sides of a ridge-ridge-ridge triple junction with the third branch as the East African Rift extending south.
Input datasets used for the development of the ARB model are property of the Saudi Geological Survey (SGS). The seismic source model for Arabian Peninsula has been constructed on the basis of recent studies related to seismic hazard assessment for the region. See Al-Arifi et al. 2013, Mohindra et al. 2012, Sokolov et al. 2017, Zahran et al 2016 for a description of the datasets used for developing the hazard model.
Seismic Source Characterisation
The Seismic Source Characterization (SSC) model consists of 29 homogeneous area source zones (Figure 1) for which seismicity parameters (occurrence, maximum magnitude, depth distribution) and dominant faulting style have been determined. The two models differ only by the occurrence parameters.
Figure 1 - The 29 seismic zones of the source model for the Arabian Peninsula.
Since two different declustering approaches (Gardner and Knopoff, 1974 and Uhrhammer 1986) have been applied to the original earthquake catalogue data, two alternative source models are made available in the logic-tree to account for epistemic variability.
Ground Motion Characterisation
The Ground Motion Characterization (GMC) model contains 7 ground motion prediction equations (GMPE). The Atkinson and Boore model (2006) is used for the stable continental region of Saudi Arabia in conjunction with the equations for active shallow crustal sources, namely: the models of Zhao et al. (2006), Boore and Atkinson (2008), Campbell and Bozorgnia (2008), and Akkar et al. (2014). The largest weight (0.60) is assigned to the Atkinson and Boore model for stable regions and equal weights (0.10) are assigned for crustal source equations. Akkar et al. (2014) suggested to consider their model for seismic hazard studies in areas where normal-faulting earthquakes dominate. Therefore, the model (weight 0.3) was used together of Pankow and Pechmann (2004) model (weight 0.7) for extensional zones in the Red Sea. The Pankow and Pechmann’ model supersedes a previous study of strong ground motions in extensional tectonic regimes by Spudich et al. (1999).
Two GMPEs developed for the volcanic region of Hawaii were used specifically for the volcanic areas (Yemen Basaltic Trap, Harrat Lunayyir Hot Spot, Makkah- Madinah-Nafud) seismic source zone. The first model is the equation obtained by Munson and Thurber (1997) on the basis of earthquake records from 22 shallow earthquakes with magnitudes from 4.0 to 7.2. The equation predicts PGA as a function of magnitude and source-to-site distance for two site conditions – lava and ash. The maximum of two horizontal components was considered in the model, therefore a coefficient 1.1 (Beyer and Bommer, 2006) is applied in our calculation for conversion to geometric mean of horizontal components that is used in all other GMPEs used in this work. The second equation was developed by Atkinson (2010). Note that the Munson and Thurber model is used for PGA, the Atkinson model for response spectra.
Figure 2 - Comparison of the ground motion predicted by the different GMPEs used in the ARB model. The plot is for spectral acceleration at 0.2 seconds and Mw 6.
The table below shows the GMC. While in the original implementation the different GMPE were defined by source, in the OQ engine the GMPEs have been clustered into four main tectonic groups: stable regions (TECTONIC_REGION_1), the Red Sea (TECTONIC_REGION_2), active shallow crust (TECTONIC_REGION_3), and volcanic (TECTONIC_REGION_4). The groups are also depicted in Figure 3. Two GMPE logic- trees are implemented, one for PGA and one for other spectral ordinates.
For every tectonic region, epistemic uncertainty is considered by using multiple GMPEs, each with an associated logic tree weight.
|MunsonThurber1997 (PGA), Atkinson2010Hawaii (SA)||0.3|
Figure 3 - Clustering of the GMPEs of the ARB model into four tectonic groups.
Hazard curves were computed in the OQ engine for peak ground acceleration (PGA) and spectral acceleration (SA) at 0.2s, 0.5s, 1.0s, and 2s. The computation was performed on a grid of 38192 sites (spaced at approximately 10 km) with reference soil conditions corresponding to a shear wave velocity in the upper 30 meters (Vs30) of 760-800 m/s.
The hazard map for PGA corresponding to a 10% probability of exceedance in 50 years (475 year return period), can be seen using the interactive viewer. For a more comprehensive set of hazard and risk results, please see the GEM Visualization Tools.
Results from the GEM implementation of the ARB model have been compared against the data provided by Dr. Sokolov from SGS at selected sites (Figure 4). Minor differences have been experienced, mostly interpretable by differences in the software used for the calculation.
Figure 4 - Comparison between results obtained from the GEM implementation of the ARB model and the original SGS results.
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