Application of the Spatially Smoothed Seismicity and Monte Carlo Methods to Estimate the Seismic Hazard of Eritrea and the Surrounding Region

Autor: Lijam Hagos, Roland Roberts, Ronald Arvidsson
Rok vydání: 2006
Předmět:
Zdroj: Natural Hazards. 39:395-418
ISSN: 1573-0840
0921-030X
DOI: 10.1007/s11069-005-6127-9
Popis: The region of interest is characterized by incomplete data sets and little information about the tectonic features. Therefore, two methodologies for estimating seismic hazard were used in order to elucidate the robustness of the results: the method of spatially smoothed seismicity introduced by Frankel (1995) and later extended by Lapajne et al. (1997) and a Monte Carlo approach presented by Ebel and Kafka (1999). In the first method, fault-rupture oriented elliptical Gaussian smoothing was performed to estimate future activity rates along the causative structures. Peak ground accelerations were computed for a grid size of 15 km x 415 km assuming the centre of the grids as epicentres, from which the seismic hazard map was produced. The attenuation relationship by Ambraseys et al. (1996) was found suitable for the region under study. PGA values for 10% probability of exceedence in 50 years (return period of 475 years) were computed for each model and a combined seismic hazard map was produced by subjectively assigning weights to each of these models. A worst-case map is also obtained by picking the highest value at each grid point from values of the four hazard maps. The Monte Carlo method is used to estimate seismic hazard, for comparison to the results from our previous approach. Results obtained from both methods are comparable except values in the first set of maps estimate greater hazard in areas of low seismicity. Both maps indicate a higher hazard along the main tectonic features of the east African and Red Sea rift systems. Within Eritrea, the highest PGA exceeded a value 25% of g, located north of Red Sea port of Massawa. In areas around the capital, Asmara, PGA values exceed 10% of g. Language: en
Databáze: OpenAIRE
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