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http://dx.doi.org/10.9765/KSCOE.2019.31.2.62

Construction of Logic Trees and Hazard Curves for Probabilistic Tsunami Hazard Analysis  

Jho, Myeong Hwan (Department of Civil and environmental engineering, Hanyang University)
Kim, Gun Hyeong (HYCERG Inc.)
Yoon, Sung Bum (HYCERG Inc.)
Publication Information
Journal of Korean Society of Coastal and Ocean Engineers / v.31, no.2, 2019 , pp. 62-72 More about this Journal
Abstract
Due to the difficulties in forecasting the intensity and the source location of tsunami the countermeasures prepared based on the deterministic approach fail to work properly. Thus, there is an increasing demand of the tsunami hazard analyses that consider the uncertainties of tsunami behavior in probabilistic approach. In this paper a fundamental study is conducted to perform the probabilistic tsunami hazard analysis (PTHA) for the tsunamis that caused the disaster to the east coast of Korea. A logic tree approach is employed to consider the uncertainties of the initial free surface displacement and the tsunami height distribution along the coast. The branches of the logic tree are constructed by reflecting characteristics of tsunamis that have attacked the east coast of Korea. The computational time is nonlinearly increasing if the number of branches increases in the process of extracting the fractile curves. Thus, an improved method valid even for the case of a huge number of branches is proposed to save the computational time. The performance of the discrete weight distribution method proposed first in this study is compared with those of the conventional sorting method and the Monte Carlo method. The present method is comparable to the conventional methods in its accuracy, and is efficient in the sense of computational time when compared with the conventional sorting method. The Monte Carlo method, however, is more efficient than the other two methods if the number of branches and the number of fault segments increase significantly.
Keywords
tsunami hazard analysis; logic trees; probabilistic modelling;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Mori, N., Goda, K. and Cox, D. (2018). Recent process in probabilistic tsunami hazard analysis (PTHA) for mega thrust subduction earthquakes. In the 2011 Japan earthquake and tsunami: Reconstruction and restoration, 469-485.
2 Musson, R.M. (1999). Determination of design earthquakes in seismic hazard analysis through Monte Carlo simulation. Journal of Earthquake Engineering, 3(4), 463-474.   DOI
3 Musson, R.M. (2000). The use of Monte Carlo simulations for seismic hazard assessment in the UK. Annals of Geophysics, 43(1), 1-9.   DOI
4 Park, H. and Cox, D.T. (2016). Probabilistic assessment of nearfield tsunami hazards: Inundation depth, velocity, momentum flux, arrival time, and duration applied to Seaside. Oregon. Coastal Engineering, 117, 79-96.   DOI
5 Rhee, H.-M., Kim, M.K., Sheen, D.-H. and Choi, I.-K. (2014). Estimation of wave parameters for probabilistic tsunami hazard analysis considering the fault sources in the Western Part of Japan. Journal of the Earthquake Engineering Society of Korea, 18(3), 151-160.   DOI
6 Shapira, A. (1983). Potential earthquake risk estimations by application of a simulation process. Tectonophysics, 95(1-2), 75-89.   DOI
7 Sugino, H., Iwabuchi, Y., Hashimoto, N., Matsusue, K., Ebisawa, K., Kameda, H. and Imamura, F. (2015). The characterizing model for tsunami source regarding the inter-plate earthquake tsunami. Journal of Japan Association for Earthquake Engineering, 15(3), 114-133.
8 The Headquarters for Earthquake Research Promotion (2003). Long-term Evaluation of seismic activity in the eastern margin of Japan sea (in japanese).
9 Yoon, S.B., Lim, C.H. and Choi, J. (2007). Dispersion-correction finite difference model for simulation of transoceanic tsunamis. Terrestrial Atmospheric and Oceanic Sciences, 18(1), 31-53.   DOI
10 Aida, I. (1978). Reliability of a tsunami source model derived from fault parameters. Journal of Physics of the Earth, 26(1), 57-73.   DOI
11 Annaka, T., Satake, K., Sakakiyama, T., Yanagisawa, K. and Shuto, N. (2007). Logic-tree approach for probabilistic tsunami hazard analysis and its applications to the japanese coasts. Pure and Applied Geophysics, 164(2), 577-592.   DOI
12 Assatourians, K. and Atkinson, G.M. (2013). EqHaz: An open-source probabilistic seismic-hazard code based on the Monte Carlo simulation approach. Seismological Research Letters, 84(3), 516-524.   DOI
13 Horspool, N., Pranantyo, I., Griffin, J., Latief, H., Natawidjaja, D., Kongko, W., Cipta, A., Bustaman, B., Anugrah, S.D. and Thio, H. (2014). A probabilistic tsunami hazard assessment for Indonesia. Natural Hazards and Earth System Sciences, 14(11), 3105-3122.   DOI
14 Cramer, C.H., Petersen, M.D. and Reichle, M.S. (1996). A Monte Carlo approach in estimating uncertainty for a seismic hazard assessment of Los Angeles, Ventura, and Orange Counties, California. Bulletin of the Seismological Society of America, 86(6), 1681-1691.
15 Cornell, C.A. (1968). Engineering seismic risk analysis. Bulletin of the Seismological Society of America, 58(5), 1583-1606.   DOI
16 Fukutani, Y., Suppasri, A. and Imamura, F. (2015). Stochastic analysis and uncertainty assessment of tsunami wave height using a random source parameter model that targets a Tohoku-type earthquake fault. Stochastic Environmental Research and Risk Analysis, 29(7), 1763-1779.   DOI
17 Japan Society of Civil Engineers (2008). Survey result on the weight of logic trees (in japanese).
18 Japan Society of Civil Engineers (2016). Tsunami assessment technique for Nuclear Power Plant 2016 (in japanese).
19 Lorito, S., Selva, J., Basili, R., Romano, F., Tiberti, M.M. and Piatanesi, A. (2014). Probabilistic hazard for seismically induced tsunamis: accuracy and feasibility of inundation maps. Geophysical Journal International, 200(1), 574-588.   DOI
20 Mansinha, L. and Smylie, D. (1971). The displacement fields of inclined faults. Bulletin of the Seismological Society of America, 61(5), 1433-1440.