The Dependency of Probabilistic Tsunami Hazard Assessment on Magnitude Limits of Seismic Sources in the South China Sea and Adjoining Basins
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The South China Sea (SCS) and its adjacent small basins including Sulu Sea and Celebes Sea are commonly identified as tsunami-prone region by its historical records on seismicity and tsunamis. However, quantification of tsunami hazard in the SCS region remained an intractable issue due to highly complex tectonic setting and multiple seismic sources within and surrounding this area. Probabilistic Tsunami Hazard Assessment (PTHA) is performed in the present study to evaluate tsunami hazard in the SCS region based on a brief review on seismological and tsunami records. 5 regional and local potential tsunami sources are tentatively identified, and earthquake catalogs are generated using Monte Carlo simulation following the Tapered Gutenberg–Richter relationship for each zone. Considering a lack of consensus on magnitude upper bound on each seismic source, as well as its critical role in PTHA, the major concern of the present study is to define the upper and lower limits of tsunami hazard in the SCS region comprehensively by adopting different corner magnitudes that could be derived by multiple principles and approaches, including TGR regression of historical catalog, fault-length scaling, tectonic and seismic moment balance, and repetition of historical largest event. The results show that tsunami hazard in the SCS and adjoining basins is subject to large variations when adopting different corner magnitudes, with the upper bounds 2–6 times of the lower. The probabilistic tsunami hazard maps for specified return periods reveal much higher threat from Cotabato Trench and Sulawesi Trench in the Celebes Sea, whereas tsunami hazard received by the coasts of the SCS and Sulu Sea is relatively moderate, yet non-negligible. By combining empirical method with numerical study of historical tsunami events, the present PTHA results are tentatively validated. The correspondence lends confidence to our study. Considering the proximity of major sources to population-laden cities around the SCS region, the tsunami hazard and risk should be further highlighted in the future.
KeywordsTsunami hazard corner magnitude Monte Carlo simulation return period South China Sea region
We appreciate the sharing of PB2002 Global Plate Model and computing codes of Maximum Likelihood method by Peter Bird and Yan Y. Kagan. COMCOT source codes developed by Philips Liu and Xiaoming Wang can be downloaded from ceeserver.cee.cornell.edu/pll-group/comcot_down.htm. EQHAZ package for Monte Carlo simulation is downloaded from http://www.seismotoolbox.ca/EQHAZ.html. We especially thank Dr. Bautista and Dr. Narag from the Philippine Institute of Volcanology and Seismology (PHIVOLCS) to provide technical report of ‘Philippine Tsunamis and Seiches (1589–2012)’, which is very useful for this study. Two anonymous reviewers also provide very useful and insightful comments on the manuscript. This study is supported by Public science and technology research funds projects of ocean (No. 201405026) and GASI-GEOGE-05.
- Bautista, M.L.P., Bautista, B.C., Salcedo. J.C. & Narag. I.C. (2012). Philippine tsunamis and seiches (1589–2012) (pp. 1–111).Google Scholar
- Ca, V. T., & Xuyen, N. D. (2008). Tsunami risk along Vietnamese coast. Journal of Water Resources and Environmental Engineering, 23, 24–33.Google Scholar
- Cornell, C. A. (1968). Engineering seismic risk analysis. Bulletin of the Seismological Society of America, 58, 1583–1606.Google Scholar
- Heidarzadeh, M., & Kijko, A. (2010). A probabilistic tsunami hazard assessment for the Makran subduction zone at the northwestern Indian Ocean. Natural Hazards, 58, 577–593.Google Scholar
- Okada, Y. (1985). Surface deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of America, 75, 1135–1154.Google Scholar
- Rangin, C., Pichon, X. L., Mazzotti, S., Pubellier, M., Chamot-Rooke, N., Aurelio, M., et al. (1999). Plate convergence measured by GPS across the Sundaland Philippine Sea plate deformed boundary: the Philippines and eastern Indonesia. Geophysical Journal International, 139, 296–316.CrossRefGoogle Scholar
- Selva, J., & Marzocchi, W. (2004). Focal parameters, depth estimation, and plane selection of the worldwide shallow seismicity with M s ≥ 7.0 for the period 1900–1976. Geochem. Geophys. Geosys. 5, Q05005.Google Scholar
- Socquet, A., Simons, W., Vigny, C., McCaffrey, R., Subarya, C., Sarsito, D., et al. (2006). Microblock rotations and fault coupling in SE Asia triple junction (Sulawesi, Indonesia) from GPS and earthquake slip vector data. Journal Geophysical Research, 111, B08409.Google Scholar
- Thio, H. K., Somerville, P., & Ichinose, G. (2012). Probabilistic analysis of strong motion and tsunami hazards in South East Asia. Journal of Earthquake and Tsunami, 2, 119–137.Google Scholar
- Wells, D. L., & Coppersmith, K. J. (1994). New empirical relationships among magnitude, rupture length, rupture width, rupture area, and surface displacement. Bulletin of the Seismological Society of America, 84, 974–1002.Google Scholar