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Tsunami Earthquake Lessons learned regarding Tsunami Hazard assessment and protection against tsunami of nuclear installations Kenji Satake Earthquake Res. Inst. Univ. Tokyo [email protected]‐tokyo.ac.jp Regional Workshop on Site Evaluation and Safety Improvement focusing on the post‐actions after Fukushima NPPs accident and Annual Meeting of the Siting Topical Group (STG) 13 June 2012, Daejeon, Korea Outline 1. Lessons learned from 2011 Tohoku tsunami 2. Probabilistic Tsunami Hazard Assessment 3. Infrequent tsunamis in the world Tsunami Damage at NPS 2011 tsunami Onagawa design tsunami height 13.6 m 13 m site level 14.8 m Fukushima‐1 design tsunami height 6.1 m 16 m site level 10‐13 m Fukushima‐2 design height 5.2 m 15 m site level 12 m Tokai design height 4.9 m 5 m site level 8.0 m Tsunami Damage at NPS Fukushima‐1 Design height 6.1 m based on 1938 Shioya‐oki earthquakes (Mw 7.9) Design height became 6.1 m in 2009 Long‐term forecast of earthquakes Along Japan trench Tsunami earthquakes Iwate 3 events in last 400 years once in 133 years somewhere in the 800 km region at particular place once in 533 yrs (fault length: 200 km) Miyagi +3m, 24 m ‐0.7m, 15 m Fuku‐ Outer‐rise normal fault eq. shima 1 event in 400 yrs once in 400 –+0.9 750 yrsm, somewhere5 m at particular place, once in 1600‐3000 yrs 869 Jogan earthquake model Long term forecast by ERC Tsunami Damage at NPS Fukushima‐1 Design height 6.1 m based on 1938 Shioya‐oki earthquakes (Mw 7.9) Tsunami earthquake Similar to 1869 off Fukushima estimated tsunami heights: 9.3 ‐15.7 m The 869 Jogan‐type earthquake estimated tsunami heights: 8.6 ‐ 9.2 m Probabilistic Method Annaka et al. (2007) Pure Applied Geophysics vol. 164 pp. 577‐592 Sakai et al. ICONE14 (2006) Logic tree for “tsunami earthquakes” Tsunami eq. 1896, 1611 No tsunami eq. in past Tsunami eq. 1677 Probabilistic Method Annaka et al. (2007) Pure Applied Geophysics vol. 164 pp. 577‐592 Sakai et al. ICONE14 (2006) Fukushima NPP Tsunami eq. 1896, 1611 No tsunami eq. in past Tsunami eq. Probability of > 10 m tsunami: 1677 50yr probability ~ 5 x 10‐3 Annual probability ~ 1 x 10‐4 (recurrence: ~10,000 yrs) Outline 1. Lessons learned from 2011 Tohoku tsunami 2. Probabilistic Tsunami Hazard Assessment 3. Infrequent tsunamis in the world Probabilistic Tsunami Hazard Analysis (PTHA) • PTHA is a methodology for estimating tsunami hazard curves (relationship between tsunami height and probability of exceedance) • Probabilistic approach is necessary because many uncertainties exist in a process of estimating tsunami heights along coasts from tsunami source models Probabilistic Seismic Hazard Assessment Probabilistic Tsunami Hazard Assessment Tsunami Source Models Tsunami sources Fault models Magnitude range Probability of earthquakes Branches for logic trees Numerical Models for tsunami generation and propagation Seafloor deformation model Tsunami propagation model Branches for logic trees Logic trees and numerical simulation Tsunami heights for fragility curve Tsunami hazard curves Final results: Fractile hazard curves Two kinds of uncertainty • Aleatory uncertainty ‐ Due to unpredictable random nature ‐ A hazard curve can be obtained by integration over the aleatory uncertainties • Epistemic uncertainty ‐ Due to incomplete knowledge and data ‐ Using logic tree approach, a large number of hazard curves can be obtained by the combination of model parameters that represent epistemic uncertainty Logic tree for tsunami height estimation Estimation Error of Tsunami Height Ergodic assumption: Temporal variance of tsunami heights can be assumed to be the same the spatial variance, which can be estimated from comparison between the observed and calculated tsunami heights. Probability density function of tsunami height: Truncated log‐normal distribution with median height (estimated from numerical simulation) and variance (=ln ). Probability of Exceedance Probability of Exceedance 1. Probability density function for water heights Lognormal distribution with median H0 and variance 2. Probability distribution for exceedance hmax 0 cal pl,i, j,k (h) p(h0;hl,i, j,k ,)t(h0 )dh0 h hmin 0 0 Plot the area for each h Making Fractile curves Annual exceedance probability Distribution for weight Sum for scenarios with probability W values for each of height h0 curve across H=h0 Cumulative line sum for weights Fractile curves Cumulative weight Plot for various h0 85% fractile 50% 15% Sum for scenarios with probability of height h0 Weights of Hazard Curves • Weights (probabilities) of branches are determined based on the future probabilities of being truth • Weight for each hazard curve is given by the products of the weights of all nodes on the path in the logic tree • Determination of weights is not a scientific problem but a problem of engineering judgment because no ones knows the correct answer in the future Logic tree representation of Uncertain Parameters Each path of logic tree generates a tsunami hazard curve Monte Carlo simulation • Number of cases can be nearly a billion ‐ Huge amount of numerical simulations • Impractical to compute all of them ‐ Hazard curves can be drawn from randomly sampled scenarios Model for PTHA in Japan 1. Identification of tsunami source zones ‐ Local tsunami source ‐ Distant tsunami sources 2. Determination of magnitude and frequency of characteristic tsunamigenic earthquakes 3. Determination of tsunami height estimation model based on numerical tsunami simulation 4. Determination of weight for branches Tsunami sources around Japan Tsunami earthquakes along Japan Trench Distant tsunami source Characteristic earthquake model • Characteristic earthquakes are assumed to occur repeated in each tsunami source • Model parameters ‐ Magnitude distribution of characteristic eq. ‐ Distribution of recurrence interval (mean and variability) ‐ Date of the most recent earthquake Logic tree for magnitude distribution ‐ Uniform distribution is assumed ‐ The band width is either 0.5 or 0.3 ‐ Branches are determined with reference to the maximum size (Mw) in the past Max eq. in the past Logic tree for mean recurrence interval In JTN1, characteristic earthquake have occurred in AD 1677, 1763, 1856 and 1968 Using the three samples of recurrence intervals, the best estimate (mean) and its error (standard deviations) are evaluated Two Temporal Models for Earthquake Occurrence • Poisson model ‐ Temporally random occurrence is assumed ‐ For long‐term stationary tsunami hazard • Brownian Passage Time (BPT) model ‐ A renewal process ‐ For instantaneous tsunami hazard ‐ Parameter for variability Tsunami Height Estimation Model 1. Numerical simulation is used for estimation of the median tsunami height 2. Fault models are determined by scaling relations from the optimal fault models of the historical tsunamigenic earthquakes for each tsunami source 3. The optimal fault models were determined from tsunami runup height data 4. Truncated long‐normal distribution is assumed for the distribution of estimation error of tsunami height. Methods of weight determination Branches are divided into two types • Branches that represent alternative hypothesis and interpretations The weights were determined by questionnaire survey of tsunami and earthquake experts (maximum 35) • Branches that represent the error of estimated parameters (for example: mean recurrence intervals) The weights were determined by error evaluation Site for PTHA (Yamada Town, Iwate Prefecture) Tsunami hazard curves (1) Tsunami hazard curves (2) Tsunami hazard curves (3) Tsunami Hazard Curves for Fukushima‐Daiichi NPS Sakai et al. ICONE14 (2006) Tsunami Hazard Curves for Fukushima‐Daiichi NPS Sakai et al. ICONE14 (2006) Probability of > 10 m tsunami: 50yr probability ~ 5 x 10‐3 Annual probability ~ 1 x 10‐4 (recurrence: ~10,000 yrs) Outline 1. Lessons learned from 2011 Tohoku tsunami 2. Probabilistic Tsunami Hazard Assessment 3. Infrequent tsunamis in the world Only five M9 earthquakes since 20th century Updated Satake and Atwater (2007, Ann. Rev. Earth Planet. Sci.) 2004 Sumatra‐Andaman earthquake Andaman‐Nicobar Is. 1941 M 7.7 1881 M 7.9 1847 M 7.5 (from historical records) 2004 M 9.1 2005 M 8.7 Sumatra 1861 M 8.5 1797 M 8.4 1833 M 8.9 (from coral studies) Paleoseismology around Indian Ocean Paleoseismological studies (corals, tsunami deposits, marine terrace, buried peat) indicate that earthquakes similar to the 2004 earthquake occurred a few hundred yrs ago. Myanmar Thailand Andaman Tamil Nadu Sumatra Tsunami deposits in Thailand 2004 tsunami ~AD1400 tsunami Sheet A: 2004 tsunami deposit Sheet B: 550‐ 700 years BP Jankaew et al. (2008 Nature ) South‐Central Chile AD1960 AD1575 ~AD1300 ~AD1100 Giant (M~9.5) earthquakes ~300 yr interval Cisternas et al. (2005 Nature) NOT ~ 100 yr as inferred from historic data Cascadia Subduction Zone Coastal paleoseismology 1990’s Photo by Brian Atwater Tsunami recorded in Japan in 1700 Fault length: 1,100 km, slip: 14 m, Mo 4.6 x 1022 Nm (Mw 9.0) similar to the 2004 Sumatra‐Andaman earthquake Average recurrence interval: ~500 years Satake, Wang, Atwater (2003, JGR) Paleoseismological studies Southeast Asia (Sumatra‐Andaman) 2004: M 9.1‐3 occurrence of similar earthquake confirmed recurrence interval ~ a few hundred to thousand years? South America (Chile) 1960: M = 9.5 1586 eq. was similar, but 1837 and 1737 were smaller average interval of M~9 event: ~ 300 yrs North America (Cascadia) 1700: M ~9.2 average interval (from paleoseismology) ~ 500 yrs Variability in subduction‐zone earthquakes Updated Satake and Atwater (2007, Ann. Rev. Earth Planet. Sci.) Summary 1. For the Fukusima‐daiichi NPS, tsunami source models other than used for the deterministic assessment were examined, but the assessment was not implemented, because the models were not officially endorsed. 2. The probabilistic tsunami hazard assessment method can handle two types of uncertainties: aleatory and epistemic. Logic‐tree approach can be adopted for equivocal choices. 3. Giant (M~9) earthquakes are rare; they occur once in several centuries in the world’s subduction zones. Hence geological studies of past tsunamis are important. .
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