平成25年度第1回総合防災セミナーのご案内

総合防災研究グループでは、平成25年度の第1回総合防災セミナーを下記の要領で開催しますので、ご案内させていただきます。お誘い合わせの上、是非ご参加いただきますようお願い申し上げます。

日時：
Date:

平成25年5月7日（火）15:00-16:30
May. 7, 2013 (Tue.) 15:00-16:30

場所：
Venue:

京都大学宇治キャンパス　研究所本館　防災研究所大会議室 S-519D
Kyoto Univ., Uji Campus, Main Building S-519D

プログラム：
Program:

15:00 - 16:30

講演者：
Lecturer:

Prof. Fabrice Cotton

講演タイトル：
Theme:

Epistemic and Aleatory Variabilities of Ground-motion Models

講演概要：
Abstract:

In order to predict future earthquakes ground-motion, we need to evaluate two types of uncertainties: uncertainties due to the lack of knowledge (“epistemic uncertainty”) and uncertainties due to the natural variability of earthquakes and wave propagation properties (“aleatory uncertainty”). In a first step, the presentation will describe the methodologies used to build a logic tree which captures the epistemic uncertainty of ground-motion prediction in Europe (new European seismic-hazard map, Delavaud et al., 2012). We will show how new accelerometric databases (e.g. Kik-Net and K-Net data) help to reduce such uncertainty by a better testing of existing ground-motion models or the development of fully data-driven models (Derras et al., 2012). In a second step we will discuss the aleatory variability of ground-motion models. One of the key challenges of seismology is to be able to calibrate and analyze the physical factors that control this aleatory variability. The exponential growth of seismological near-field records (e. g. Kik-Net data) provides the opportunity to separate the source, propagation, and site factors controlling the ground-motion variability (Rodriguez et al., 2011). Our data analysis shows that some stations are also showing a larger variability of ground-motions than others and that moderate earthquakes are more ‘variable’ for a given magnitude than large ones. We suggest (Cotton et al., 2013) that the between-event ground-motion variability gives an upper bound of the earthquake stress-drop variability. This quantification of stress-drop variability may offer a new way to calibrate future earthquakes ground-motion simulations.

References
Cotton, F., Archuleta R. and M. Causse. What is sigma of stress drop ? 2013.
Seismological Research Letter, 84, doi:10.1785/0220120087
Derras, B., PY Bard, F. Cotton and A. Bekkouche. Adapting the Neural Network
Approach to PGA Prediction: An Example Based on the KiK-net Data. 2012.
Bulletin of the Seismological Society of America, 102, doi: 10.1785/
0120110088
Delavaud, E., F. Cotton, S. Akkar, F. Scherbaum, L. Danciu, C. Beauval, S.
Drouet, J. Douglas, R. Basili, A. Sandikkaya, M. Segou, E. Faccioli and N.
Theodoulidis, 2012. Toward a Ground-Motion Logic Tree for Probabilistic
Seismic Hazard Assessment in Europe. Journal of Seismology. DOI 10.1007/
s10950-012-9281-z
Rodriguez-Marek, A., Montalva, G.A., Cotton, F. and F. Bonilla. Analysis of
Single-Station Standard Deviation Using the KiK-net data, 2011. Bulletin of
the Seismological Society of America, 101, 1242-1258, doi: 10.1785/
0120100252

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