Probabilistic Seismic Hazard Analysis - Japanese intensity map and

Transcription

1 H4.SMR/ "Workshop on the Conduct of Seismic Hazard Analyses for Critical Facilities" May 2006 Probabilistic Seismic Hazard Analysis - Japanese Intensity Map and Prospective Yoshi FUKUSHIMA Shimizu Corporation, Tokyo, Japan

2 Probabilistic Seismic Hazard Analysis - Japanese intensity map and prospective Yoshi. FUKUSHIMA Base on In detail: Tech Note, NIED, 275 (in Japanese) 1

3 Relation between I JMA and others V - V + VI - VI + Comparison of seismic intensity scales (Reiter, 1999; Murphy and O Brien, 1977; Richter, 1958); MM Modified Mercalli; RF Rossi-Forel; JMA Japanese Meteorological Agency; MCS Mercalli-Cancani-Sieberg; MSK Medvedev-Sponheuer-Karnik 2

4 contents Introduction Source categories and Hazard curve Source modeling Strong motion estimation Classification of ground condition Results Uncertainty Consideration of recent earthquakes Application to critical facilities 3

5 Introduction The establishment of the Headquarters for Earthquake Research Promotion The Great Hanshin-Awaji Earthquake Disaster on January 17, 1995 killed nearly 6,400 people and destroyed over 100,000 buildings, and brought to light a number of problems in our national earthquake disaster prevention measures. Following on the lessons learned from this disaster, the Special Measure Law on Earthquake Disaster Prevention sponsored by legislators was enacted in July 1995 to promote a comprehensive national policy on earthquake disaster prevention. The failure to sufficiently communicate and apply earthquake research results to the general public and disaster prevention organizations highlighted the need for a direct system of accountability in government policy regarding earthquakes, and the Headquarters for Earthquake Research Promotion, a special governmental organization attached to the Prime Minister's office(now belongs to the Ministry of Education, Culture, Sports, Science and Technology), was established in accordance with this law. 4

6 National budget used for earthquake research The fiscal year 2005 governmental budget allocation related to the Headquarters for Earthquake Research Promotion is approximately 66 million EUR* (102% compared with last year). *Excludes a grant of operating costs to independent administrative institutions and National University Corporations. 5

7 Structure of the Headquarters for Earthquake Research Promotion 6

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9 Source categories a) 98 main active faults b) Subduction zone characterized earthquakes c) Others 1 Other active faults than 98 2 Uncertain sources (1)Subduction events other than the characterized earthquakes (2)Intra-plate events other than the characterized earthquakes (3)Crustal earthquakes not associated with active faults (4)Specific regions of Urakawa, East-end of Japan-sea, South of Izu islands, and Nansei-shoto Islands Probability of magnitude, distance and occurrence 8

10 Hazard curve Period Probability of exceedance Intensity of JMA P ( Y > y; t) k Probability of exceedance of intensity y in t years P ( Y > y; t) = 1 {1 Pk ( Y > y; t)} k where is probability exceeding intensity y in t years by k-th event (or events group). 9

11 (1)Expected sources a) Time predictable P k ( Y > y; t) = = P( E P( E k k ; t) P( Y ; t) > P( Y > i j y a) 98 main active fault b) Subduction zone giant earthquakes c) Others 1 Other active faults than 98 E k ) y m i, r j ) P k ( m i ) P k ( r j m i ) P k P k (m i ) ( rj mi ) is distribution function of probability of magnitude m i by k-th event. is distribution function of probability of distance for given mi. Y (m i,r j ) P(Y > y m i,r j ) is probability of exceedance of y for given mi and ri. P(Y > y m i,r j ) = 1 F U y Y (m i,r j ) mean value of y and uncertainty of U, ordinary log normal distribution, can be assumed. F U (u) is distribution function of summation of U. 10

12 Stress Loading Probability of occurrence of k-th event in next t years Assumed to be BPT (Brownian Passage Time ) distribution Classical View: Uniform Loading Stress Loading EQ EQ Stress Loading Time Stress Loading EQ EQ Stress Loading Stress Loading Reality: Transient Loading Stress Loading Stress Loading Stress Loading Stress Loading EQ From Andrew J. Michael (USGS) EQ EQ EQ Time How does the loading curve affect the statistics of earthquake recurrence? 11

13 Brownian Passage Time Model of Earthquake Recurrence Kagan & Knopoff (1987), Matthews et al. (2002) Uniform Loading Brownian Noise Level None Little More 12

14 Here after, noise is α or uncertainty. 13

15 Case of return period 1000 years and last event was 700 years before. Geological survey Return period BPT with α 30years Last event At present year Probability of occurrence in next 30 yeas=area b/(b+c) 14

16 Return period 100years for Subduction earthquake probability(%) Return period 1000years for active fault years year Difference of probability between subduction earthquake and active fault 15

17 16 b) Poisson process is annual frequency of exceedance of y by k-th event. is annual frequency of occurrence of k-th event P k (Y > y;t) =1 exp{ ν k (Y > y) t} ν k (Y > y) ( ) > = > = > i i j k i k j j i k k k k m r P m P r m y Y P E E y Y P E y Y ) ( ) ( ), ( ) ( ) ( ) ( ν ν ν ν( E k )

18 (2) Unexpectable event groups c) Others 2 Uncertain sources (1)Subduction events other than the giant earthquakes (2)Intra-plate events other than the giant earthquakes (3)Crustal earthquakes not associated with active faults (4)Specific regions of Urakawa, East-end of Japan-sea, South of Izu islands, and Nansei-shoto Islands Probability of exceedance of intensity y by n-th event group in t years: P n ( Y > y; t) = 1 exp{ ν ( Y > y) t} n ν n (Y > y) is annual frequency of exceedance of y by n-th group. 17

19 18 is annual frequency of occurrence of k-th event in a region of event group. minimum magnitude is 5.0 (Summation of eq ) Distribution of magnitude is corresponding to Gutenberg-Richter relation with maximum magnitude (truncated b-value model) Gutenberg-Richter relation : ( ) > = > = > k i i j k i k j j i k k k k n m r P m P r m y Y P E E y Y P E y Y ) ( ) ( ), ( ) ( ) ( ) ( ν ν ν N(M m)=10 a bm

20 Therefore, distribution function of M is Where ml and mu are minimum and maximum M respectively. Probability of mi is Where, m1 and m2 are boundary of discrete magnitude range. 19

21 Expected sources modeling Unexpectable event groups site site site Probability of M, distance and occurence summation Probability of exceedance in t years intensity 20

22 If probability of exceedance is fixed, we can estimate intensity. Probability of exceedance in t years If intensity is fixed, we can estimate probability of exceedance. t is 30 and 50 years. intensity 21

23 Source modeling for PSHA a) 98 main active faults Activity A: 1mm/year B: 0.25mm/year C: 0.1mm/year unknown activity=b Both recent event and activity is unknown: Poisson Return period and recent event may have range of uncertainty. Average and maximum cases are considered. Possibility of several rupture lengths is expected, maximum lengths are assumed If dip angle is unknown, 90 degrees for strike-slip and 60 degrees for dip (and normal) -slip are assumed. Width of fault plane corresponding to seismogenic zone, and upper depth of the zone assumed to be 3km. Specific case of Futagawa-Hinage fault was applied logic tree. 22

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26 name slip Max M length width dipangle Seismogenic zone Long term evaluation by experts Modeled parameters 25

27 Same time independent independent weight Probability and M Ave Max Ave Max 26

28 b) Subduction zone characterized earthquakes Blue region 27

29 Region Nankai M Return period Recent event Uncertainty 30years 50years Long term evaluation by experts BPT model Tounankai Souteitoukai 28

30 Probability of occurrence of dependent and independent on individual region Nankai Tounankai Souteitoukai 29

31 ア and オ Miyagiken-oki Mj7.2 Region ア Region オ North-east Japan and Pacific plate subduction zone, except Hokkaido Events history 30 Possibility of twice in 50 years is considered.

32 Inter plates Intra plate 31

33 b) Subduction zone characterized earthquakes (as giant events) b) Subduction zone characterized earthquakes (as smaller events than giant event) 40km 40km 60km 60km ソースを置く位置であって Mw とは無関係 Type of 1968 M~8.0 Tokachi-oki Return period is ~100? G-R: b=0.9, Poisson model return period of 11.3 years for Mw=7.1: 26.3%~Mw=7.6: 9.3% (relative) 30 years: 93% ; 50 years: 99% 32

34 c) Others 1 Other active faults than 98 Basically, fault length larger than 10km, and if distance up to next fault less than 5km means continued fault. Poisson process and return period R is as follows R=1000 D/S Where, D is dislocation of rupture in m, and S is average dislocation per year in mm/y. Empirical relations of M: logl=0.6m-2.9 logd=0.6m-4.0 are determined by Matsuda(1975), where L is fault length in km Therefore, R can be evaluated with L and S as logr=log(l/s)

35 Degree of fault activity is defined as follows: If S is evaluated, evaluated value is adopted, otherwise, A: 1 mm/year A~B: 0.5 mm/y B: 0.25 mm/y B~C: 0.1mm/y C: 0.047mm/y For undefined and less than above, 0.024mm/y is assumed. Dip angle of 90degree is assumed for all. Top of fault plane is assumed to be at 3km. Total of 178 faults 34

36 name L Return period Occurrence Probability Darks are 98 main and reds are 1 Other active faults than 98 35

37 Darks are 98 main and reds are 1 Other active faults than 98 36

38 c) Others 2 Uncertain sources (1)Subduction events other than the characterized earthquakes (2)Intra-plate events other than the characterized earthquakes (3)Crustal earthquakes not associated with active faults (4)Specific regions of Urakawa, East-end of Japan-sea, South of Izu islands, and Nansei-shoto Islands Two source zonings were applied: Corresponding to long term evaluation and mesh on 0.1 degree of coordinate (finally, average of both was taken) Two historical earthquake catalogs were prepared. 1885~1925: greater or equal M ~2002: greater or equal M5.0 (medium events catalog) 1983~2002: greater or equal M3.0 (small events catalog)* *M4.0 for Pacific and Philippine sea plates Characteristically modeled events are eliminated. b of G-R is assumed to 0.9. and Poisson process is assumed. 37

39 An example for (3) Crustal earthquakes not associated with active faults Medium and small events catalogs were used. Focal depth shallower or equal 25km (except Japan sea region is 40km due to accuracy) Modeled events are assumed to be 3km of focal depth. Overlapped regions with other modeled area are eliminated. Mj was transmitted to Mw by following empirical equation: Mw=0.78Mj+1.08 (???) Four cases for frequency distribution of occurrence Two source zonings Two catalogs 38

40 24 source areas 39

41 Distribution of epicenters for M 5.0 after 1926, and for M 3.0 after

42 M-n distribution of medium events catalog, and small events catalog (region 8) 41

43 Assumed maximum magnitude 42

44 Annual frequency of occurrence in mesh on 0.1 degree of coordinate. Zoning boundaries are also indicated for a comparison. (M greater or equal )

45 Particular considerations for specific regions of Urakawa, Eastend of Japan-sea, South of Izu islands, and Nansei-shoto Islands For an example of Urakawa: Mantle wedge Crustal Urakawa region Upper bound of Pacific plate Annual frequency of occurrence in mesh on 0.1 degree of coordinate. 44 (M greater or equal 5.0)

46 Strong motion estimation Intensity of Japan Metrological Agency is publicly acceptable. However, we do not have any precise attenuation relation of intensity. Prof. Midorikawa attempted to convert from PGV to surface intensity. However, you can imagine that data of PGV is less than PGA, and to determine reliable regression coefficients is impossible. Therefore, he provided his best estimate of main coefficients for PGV attenuation relation. 45

47 PGV for Vs=600m/s is estimated by a specific attenuation relation. (Si&Midorikawa, 1999) Amplify 31% to PGV for Vs=400m/s (Matsuoka&Midorikawa, 1994) Amplify from Vs=400m/s to surface with empirical relations, explained in next session.!!! For some categories of hard geology, it will be de-amplification. Convert from PGV to Intensity (Midorikawa et al., 1999) 46

48 Si&Midorikawa (1999) Observed PGV at surface is decreased by applying next equation to Vs=600m/s. Where, PGV b600 is Peak Ground Velocity (cm/s) at Vs=600m/s, D is focal depth (km), and X is distance (km) that is the closest for large and hypocentral for small events respectively d is coefficient for source type: 0 for crustal, for inter plate and 0.12 for slab events -Distance coefficient is hypothesized. -Saturation coefficient of M is hypothesized. -Magnitude coefficient determined without any advanced statistical analysis, -and assumed model is liner function of single parameter M. (Just try and error scheme) Without any residual confirmation for parameters Reliability??? 47

49 Matsuoka&Midorikawa (1994) log ARV = log AVS (100 < AVS < 1500) Where AVS is average shear wave velocity from surface to depth of 30m, ARV is amplification factor : ratio between ARV of AVS=600 and that of other AVS 48

50 Midorikawa et al. (1999) Where PGVs is PGV at surface, and Iinstr is intensity calculated from strong motion records. Before 1996, intensity was decided by people at meteorological agency stations or damages. After that, it is calculated from 3 components of accelerometer, which are filtered corresponding to mean characteristic between acceleration and velocity. (so called instrumental intensity) 49

51 Trimmings Mw of crustal event is converted from Mj by an empirical relation of Takemura (1990). Anomalous seismic intensity in northeast Japan regarding to High-Q of Pacific plate subduction is corrected with following correction terms. 50

52 An empirical relation of Takemura (1990). Mw=0.78Mj Noubi Earthquake Almost one large event constrains the equation. However, Mj should be saturated in large magnitude. 51

53 Anomalous seismic intensity in northeast Japan regarding to High-Q of Pacific plate subduction is corrected with following correction terms. log V 1 = ( R tr ) (H-30) V 2 = max{ 1.0, (R/300) } } Where Rtr is distance from site to Japan trench. R is hypocentral distance. H is focal depth. V1 is applied for events deeper than 30km. V2 is extending scheme to apply Si&Midorikawa relation beyond 300km of out of data range. 52

54 epicenter Left: observed peak amplitudes Center: predicted amplitude without corrections of V1 and V2 Right: predicted with the corrections 53

55 Uncertainty Assumed to be amplitude dependent: lower dispersion for higher amplitude (really?) σ in base 10 logarithm Truncate above and below 3*σ Standard error of Si&Midorikawa Hypothesized value PGV at Vs=600m/s 54

56 Classification of ground condition Each 1km 1km This may be most advantage for mapping 55

57 56

58 Three tectonic regimes (E) North East (C) Central (W) South West Itoigawa-shizuoka tectonic line Tanakura tectonic line Median tectonic line 57

59 Empirical equation region Number of data Before Pliocene Pliocene except granite Quaternary volcanic Hill Gravel plateau uncertainty Loam Fan Sand bank And where H: altitude (m) D: distance from river Flat bottom in valley Natural bank Delta Man made Reclaimed 58

60 Before Pliocene Pliocene except granite Quaternary volcanic Hill Gravel plateau Loam If AVS less than 100m/s was estimated, it is assumed to be 100m/s. Fan Sand bank Flat bottom in valley Natural bank Man made Reclaimed Altitude (m) Delta Distance from river Vertical axis is AVS Horizontal axis is altitude except bottom, and the bottom is distance from river Dark lines are determined in 1995 Blue: East Red: Central Green: West 59

61 Then convert from AVS to amplitude As well as an empirical equation Where ARV is amplitude from at depth of 30m to surface. And assumed base rock AVS is 600m/s. 松岡 翠川 (1994) Therefore, 31% decreased corresponding from 600 to 400m/s of AVS You can expect large uncertainty in this empirical equation, and relation between 600 and 400m/s of AVS is unclear. 60

62 Results: maps Initiation date: or 50 years Intensity or Probability 61

63 Amplification Surface amplitude above Vs=400m/s Probability of exceedance of 3% in 30years Average case Peak ground velocity at Vs=400m/s 62

64 = Probability of exceedance of 3% in 30years Average case Peak ground velocity at surface Probability of exceedance of 3% in 30years convert Intensity Average case 63

65 intensity intensity Probability of exceedance of 3% in 30years Probability of exceedance of 6% in 30years 64

66 intensity intensity Probability of exceedance of 3% in 30years Probability of exceedance of 3% in 30years Average case Maximum case 65

67 By 98 main active faults intensity intensity Probability of exceedance of 3% in 30years Average case Probability of exceedance of 3% in 30years Maximum case 66

68 By subduction zone events By others intensity intensity Probability of exceedance of 3% in 30years Probability of exceedance of 3% in 30years 67

69 intensity probability Hazard for a fixed probability of exceedance of 6% in the next 30years Hazard for fixed intensity of exceedance of 5.5 (6 弱 ) in the next 30 years 68

70 By 98 main active faults probability probability Probability of exceedance of intensity 5.5 (6 弱 ) in next 30 years Average case Probability of exceedance of intensity 5.5 (6 弱 ) in next 30 years Maximum case 69

71 By subduction zone events By others probability probability Probability of exceedance of intensity 5.5 (6 弱 ) in next 30 years Probability of exceedance of intensity 5.5 (6 弱 ) in next 30 years 70

72 intensity intensity Probability of exceedance of 6% in 30years Probability of exceedance of 10% in 50years 6% / 30 years 10% / 50 years 71

73 By 98 main active faults (Maximum case) intensity intensity Probability of exceedance of 3% in 30years Probability of exceedance of 5% in 50years 3% / 30 years 5% / 50 years 72

74 By subduction zone events Probability of exceedance of 3% in 30years Probability of exceedance of 5% in 50years 3% / 30 years 5% / 50 years Why not equal? : Because of time predictable model 73

75 Deaggregation Where Ck(p,t) is influence factor for t years exceedance of hazard level p by k-th event. Pk(Y>y,t) is probability of ground motion exceeding level y by k-th event in t year 74

76 Subduction zone 98 main active faults Other type Probability exceedance (50years) intensity Average Max Percentage of contribution to hazard (5% in 50 years) Tokyo 75

77 Subduction zone 98 main active faults Other type Probability exceedance (50years) intensity Average Max Percentage of contribution to hazard (5% in 50 years) Osaka 76

78 Slab event in Philippine sea plate Slab event in Pacific plate Nankai Trough interface Crustal event 98 main active faults Southern Kanto M7 Great Kanto earthquake Intensity Influence factor (%) (Average case) At Tokyo 77

79 Crustal event Slab event in Philippine sea plate 98 main active faults Nankai Trough interface Intensity Influence factor (%) Osaka 78

80 Uncertainty Assumed to be amplitude dependent: lower dispersion for higher amplitude (really?) σ in base 10 logarithm Truncate above and below 3*σ Standard error of Si&Midorikawa Hypothesized value PGV at Vs=600m/s 79

81 Uncertainty in ground motion preditcion A priori weighting scheme X 25km 6times 25<X 50 3times 50<X times These weights are indicated in another paper, And the residuals discussed in this separate paper. With this weight, data in short distance constrains large amplitude of the relation. I shall indiate residual plots. 80

82 N events were occurred in a limited area. Aleatoric uncertainty of strong motion record of high density observation network in Japan Ej Dij Si Strong motion records from these events were observed at several sites. N Site coefficient is expressed: Si = log O ij log P( M j, Dij) j= 1{ } Where, Mj is moment magnitude of j-th event Ej, Dij is closest distance from Ej to i-th site Si, P(Mj, Dij) is predicted amplitude for Mj and Dij, and Oij is strong motion record from Ej at Si. Dij constant for all events at i-th site. ( ) log P M j, D ij Si log O + ij Aleatoric uncertainty N Epistemic uncertainties of source effect was reduced by using only events from a limited area, path effect was reduced by using only records from the limited area at specific sites, and site effect was reduced by using averaged error at the specific site. 81

83 Removing epistemic uncertainty Data selection Several events in narrow region At least 5 records at a station Station correction Averaging residual between observed and predicted at the station Reduce the station correction then estimate the residual again Circles are epicenters and triangles are stations 82

84 Intra event errors are less than 0.2. However, amplitude dependence is opposite to Midorikawa&Otake. Residuals for individual periods and peak values in each areas Relation between residuals and predicted amplitudes 83

85 Total hazard Effect of truncation 84

86 By subduction earthquakes New Uncertainty 0.20~0.15 (function of frequency) Truncated above&below 3σ Old Uncertainty 0.23 of attenuation relation Without truncation Red region in southern coast was wider than new one. 85

87 Consideration of recent earthquakes Tokachi-oki Mj Miyagi-ken-oki Mj Chuetsu, Niigata Mj Fukuoka-seihou-oki M7.0 86

88 before 30 year after Off Tokachi EQ (Identified fault zone) after Probability of exceedance of intensity 5.5 (6 弱 ) in next 30 years 30 year after

89 Off Tokachi EQ 30 year after year after 2005 intensity Total hazard at Kushiro intensity Hazard at Kushiro from Tokachi-oki source zone In 30 years; 66% 0.15% 88

90 Probability of exceedance (30years) Other than subduction Other subduction before Tokachioki after Percentage of contribution to hazard 30 year after year after

91 Chuetsu EQ. Kawaguchi Ojiya (unknow fault zone) Probability of exceedance (50years) Max Average Nagaoka Tokamachi Comparison between hazard curves and observed intensities 90

92 Hazard curves at 4 stations, where over 5.5 of intensity was observed intensity Probability is less than about 1% at all stations. Probability of exceedance of 10% in 50years (less than intensity 5.0) Observed Off Fukuoka EQ. (Mj7.0) 91

93 Application to Critical Facilities PSHA is strongly recommended by safety authority (Nuclear Safety Commission of Japan). However, it did not result in complete adoption. Japan Nuclear Energy Safety Organization prepared PSHA tools and performed case studies for 4 NPP sites. Seismic fragility evaluation up to Core Damage Frequency beyond PSHA Individual electric power companies might inspect PSHA by themselves. 92

94 Rupture initiation Modeling is applied to probabilistic approach. Number of asperity Stress drops modeling simulation Time history Logic tree Parenthesized value is weight. Probability of annual exceedance Hazard curve Tech. Note NIED No.258 PGA 93