SSS04-P01

日本地球惑星科学連合2016年大会

Probabilistic seismic hazard analysis on long fault source*ChengYu Pan1, YuanChei Wu1
1.INER
When we are defining the geometry of a long fault source in PSHA, we seek for the geological or
geophysical evidence. In a complex tectonic environment such as plate boundary region, the definingof the fault is important, thus logic tree combining the evidence of existing geological or
geophysical survey is added in. We then use these facts to divide a fault system into severalsegments or defining two faults individual even though they are close to each other. But we often
face a situation that the earthquake does not always occur on existing fault. And sometimes themagnitude of an earthquake does not go with the length of a fault as we expected. It seems like theapplying of logic tree may still miss some of the possibility of one source due to theincompleteness of field survey. However, as we know that the principle of PSHA already considered
the possibility of different size of length and magnitude of a fault. So, another way to describe along fault source is to consider the fault system as a whole and setting up a range of length andmagnitude.
In this study, we apply both method mentioned above to two cases in Taiwan. One is on the east
boarder of Taiwan, the Longitudinal Valley fault. The other located in Taiwan Strait is called
Binhai fault. And the comparison of these two methods will be shown as result.
Keywords: Probabilistic Seismic hazard analysis©2016. Japan Geoscience Union. All Right Reserved.

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日本地球惑星科学連合2016年大会

Physical equations for calculating fault-to-site distances used in NGA GMPEs based onearthquake source geometry*xiaoliang zhang1, yushan zhang1
1.China earthquake disaster prevention center
NGA GMPEs (NGA-West1, 2008 and NGA-West2, 2014) are beginning to be widely used in seismic hazard
analyses. However, these new models are considerably more complicated than previous GMPEs, and theyrequire several more input parameters. Users are faced with the challenge of estimating unknown
input parameters when implementing NGA models.
In this paper, we are interested in fault-to-site distances parameter. Scherbaum et al. (2004)(termed “SSC04”) ever developed empirical expressions for converting source-to-site distancemeasures using simulated source geometries. The conversion equations are in the form of polynomial
functions of M, RJB, and style of faulting. Kaklamanos et al. (2011) (termed “KBB11”) derived
physical equations relating the three distance measures (RJB, RRUP, and RX) found in the NGA 2008
models using various geometric principles. KBB11 used the Joyner-Boore distance (RJB) as theprimary distance measure to compute other distances (RRUP, RX) by characterizing the earthquake
source by the geometric parameters down-dip rupture width (W), depth-to-top of rupture (ZTOR), faultdip (), and source-to-site azimuth (alpha). When RX is also needed (as in the AS08 and CY08
models), KBB11 method is advantageous, because RX cannot be estimated using the SSC04 relationships(because RX had not yet been introduced as a distance measure in 2004). One other potential issue
is that the SSC04 equations are technically only applicable for RJB<100 km, whereas KBB2011
equations are physically derived and are applicable for any distance range at which the flat-earth
assumption is valid (typically, several hundred kilometers).
KBB11 used the Joyner-Boore distance (RJB) as the primary distance measure to compute otherdistances (RRUP, RX). But in one situation RJB is equal to zero, which means the site is locateddirectly above the ruptured area; either RX or RRUP must be specified in order to calculate thethird distance parameter using KBB11. In some other situations, when the fault trace and site
location is known, we need to simulate the ground motion caused by different segment rupture of thewhole entire fault. In these cases, the RX and RXY are easily measured by GIS tools but the RJB isdependent on the down-dip rupture width (W). In this paper we introduce a new distance measure RXY(the closest distance from top of rupture) which is used to estimate source-to-site azimuth alpha(sin(alpha)= RX/ RXY) and RY (RY= RXY·cos()). Based on KBB11 we derived distance equations using theRX and RXY to compute RJB, RRUP, RX, and RY0.
Keywords: NGA GMPEs, source-to-site distances, RJB©2016. Japan Geoscience Union. All Right Reserved.

- SSS04-P02 -SSS04-P02©2016. Japan Geoscience Union. All Right Reserved.

日本地球惑星科学連合2016年大会- SSS04-P02 -SSS04-P03

日本地球惑星科学連合2016年大会

地震動観測とアメリカ地質調査所地震動予測地図の比較
A comparison of USGS National Seismic Hazard Maps with observed ground motions*Mak Sum1、Schorlemmer Danijel1*Sum Mak1, Danijel Schorlemmer1
1.ドイツ地球科学研究所
1.Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum GFZ
2000年から観測された地震動と、USGSの確率論的地震動予測との比較を行った。カリフォルニアでは、観測と予測の最大加速度超過総量は一致していたが、最大応答加速度(1秒)の観測された超過総量は予測より少ないと評価された。アメリカ東部では、観測と予測が一致していると評価された。仮説検定の検出力を用いて、地震動予測地図の統計検討の実用性について議論する。
キーワード：確率論的地震動予測
Keywords: Probabilistic seismic hazard assessment©2016. Japan Geoscience Union. All Right Reserved.

- SSS04-P03 -SSS04-P04

日本地球惑星科学連合2016年大会

確率論的地震ハザード評価における認識論的不確実さの考慮に関する検討
A study on introducing epistemic uncertainties to National Seismic Hazard Maps for Japan
*森川 信之1、藤原 広行1、宮腰 淳一2、大島 光貴2、森井 雄史2*Nobuyuki Morikawa1, Hiroyuki Fujiwara1, Jun'ichi Miyakoshi2, Mitsutaka Oshima2, Takeshi Morii2
1.防災科学技術研究所、2.清水建設
1.National Research Institute for Earth Science and Disaster Prevention, 2.Shimizu Corporation
After the 2011 great Tohoku earthquake, consideration of epistemic uncertainties in seismic hazard
assessment has been one of the most important problems in Japan. In this study we show an exampleof the probabilistic seismic hazard assessment which considered epistemic uncertainty.
In National Seismic Hazard Maps for Japan published by Earthquake Research Committee of Japan(ERCJ), epistemic uncertainties such as probability of earthquake occurrence, modeling of fault
geometry, modeling of earthquake activity are partially taken into consideration, in accordancewith the long-term evaluation. If enough information is lack in long-term evaluation, then certain
measures should be taken against epistemic uncertainties, by taking complementary information intoaccount. However, the current seismic hazard assessment does not meet such demands. In our study,
we show an example of treatment of such uncertainty in modeling the probability of simultaneous
activity of multiple segments and resultant seismic hazard.
In the new version of long-term evaluation of active faults by ERCJ, probability of earthquake
occurrence caused by simultaneous activity of multi-segment faults are indicated as “unknown”. Asto these multi-segment faults events, two models shown below are proposed (Oshima et al., 2015).
Model1: Assign probability of earthquake occurrence for each segment's independent activity tomulti-segment faults events.
Model2: Assign occurrence frequency of each segment estimated by average slip velocity tomulti-segment faults events.
The model1 takes into account the long-term evaluation saying that “the probability of earthquake
occurrence does not become larger than that of each segment’s independent activity”. Thus, theprobability for multi-segment faults events that contain the segment with zero-probability ofoccurrence are also set to zero. However, the activities of neighboring segments have the potential
to trigger the event at the segment where the possibility of independent activity is evaluated as“almost zero”. In model2, probabilities for such events are not set to zero.
As to the results of hazard analysis for aforementioned two models, the difference in hazard curves
can be seen only in quite low probability range (e.g., exceedance probability of 0.1% in 30 years).
Because information on rare events tend to be short and indicated as “unknown” in long-term
evaluation, modeling with consideration of epistemic uncertainty is essential to take aim at hazard
analysis that calls extremely rare events into account.
キーワード：確率論的地震ハザード評価、認識論的不確実さ、地震活動モデル、全国地震動予測地図
Keywords: Probabilistic seismic hazard assessment, Epistemic uncertainty, Seismic activity model,
National Seismic Hazard Maps for Japan©2016. Japan Geoscience Union. All Right Reserved.

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