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Central Chile is exposed to tsunami hazard, and large earthquakes and tsunamis have occurred over the last 500 years. Tsunami hazard analysis in Chile has been traditionally implemented by means of a deterministic approach, which is based on historical events and uniform slip distribution. The objective of the present study is to improve tsunami hazard analysis in central Chile (30°S to 38°S). To encompass the purpose, stochastic earthquake scenarios of magnitude M w 8.8 to 9.2 were generated. Two different sets of stochastic tsunami scenarios were selected by means of the Stochastic Reduced Order Model (SROM), which were applied to Quintero bay to perform a Probabilistic Tsunami Hazard Analysis (PTHA). The results showed that PTHA of Quintero bay from stochastic tsunami scenarios agrees with paleotsunami records in the bay, while a deterministic tsunami scenario underestimated the hazard. Two sets (50 and 100 scenarios, respectively) give similar results when smaller return periods are analyzed. However, for larger return periods ( > 2000 yr) the set of 100 scenarios show better results consistent with previous paleoseismological findings. The methodology implemented here can be replicated in other seismic regions in Chile as well as in other active subduction zones, thus, both near field and far field events can be analyzed. [ABSTRACT FROM AUTHOR]

Regional and global tsunami hazard analysis requires simplified and efficient methods for estimating the tsunami inundation height and its related uncertainty. One such approach is the amplification factor (AF) method. Amplification factors describe the relation between offshore wave height and the maximum inundation height, as predicted by linearized plane wave models employed for incident waves with different wave characteristics. In this study, a new amplification factor method is developed that takes into account the offshore bathymetry proximal to the coastal site. The present AFs cover the North-Eastern Atlantic and Mediterranean (NEAM) region. The model is the first general approximate model that quantifies inundation height uncertainty. Uncertainty quantification is carried out by analyzing the inundation height variability in more than 500 high-resolution inundation simulations at six different coastal sites. The inundation simulations are undertaken with different earthquake sources in order to produce different wave period and polarity. We show that the probability density of the maximum inundation height can be modeled with a log-normal distribution, whose median is quite well predicted by the AF. It is further demonstrated that the associated maximum inundation height uncertainties are significant and must be accounted for in tsunami hazard analysis. The application to the recently developed TSUMAPS-NEAM probabilistic tsunami hazard analysis (PTHA) is presented as a use case. [ABSTRACT FROM AUTHOR]

Wu, E.C.; Chen, Y.L.; Wu, H.L.; Hu, K.C.; Hsiao, S.C., and Wu, Y.C., 2018. Incorporating Tidal Uncertainty into the Methodology of Probabilistic Tsunami Hazard Analysis. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 691–695. Coconut Creek (Florida), ISSN 0749-0208. The Circum-Pacific Belt has become active in recent years, and the earthquake in the border area of land and sea probably causes tsunami disaster. The hazard includes overflow flooded, building damage, casualties, and radiation crisis of nuclear power plant. To quantify the risk, probabilistic tsunami hazard analysis (PTHA) serves as a robust methodology. The uncertainty stemming from the deviation of modeling, named aleatory uncertainty, is considered with including the tidal effect on the tsunami. To deal with the aleatory uncertainty, we incorporate tidal uncertainty into PTHA. Different static tidal stages are set in Cornell Multi-grid Coupled Tsunami model (COMCOT) to evaluate tsunami hazards. Three kinds of method are presented. One could apply theoretical probability distribution to different maximum wave height by the Gaussian Method. On the other hand, the Δt method and the Pattern Method combine tsunami events with a typical year of tidal record. The difference between these methods are discussed, and the Pattern Method is regarded as the most rigorous way. Finally, the method of incorporating tidal uncertainty into PTHA has been established and been utilized to Maanshan nuclear power plant in Taiwan. [ABSTRACT FROM AUTHOR]

Wu, E.C.; Ma, W.H., Chen, Y.L.; Wu, H.L.; Hu, K.C.; Hsiao, S.C. and Wu, Y.C., 2016. Probabilistic Tsunami Hazard Analysis - Application to Maanshan Nuclear Power Plant in Taiwan. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 1267 - 1271. Coconut Creek (Florida), ISSN 0749-0208. In the past twelve years, two earthquakes of magnitude 9.0 have occurred in the western Pacific. These earthquakes resulted in tsunamis, causing tremendous casualties, such as the nuclear disaster in Japan on March, 2011. Taiwan is an island located in the circum-Pacific belt, along which approximately 90% of the world's largest earthquakes take place. To prevent hazards, probabilistic tsunami hazard analysis (PTHA) is applied to nuclear power plants in the coastal regions of Taiwan. The approach developed here allows for the selection of reasonable tsunamis generated from distant earthquakes in the Manila Trench. Two types of uncertainty are considered: aleatory uncertainty and epistemic uncertainty. Concerning the aleatory uncertainty of modeling, a validation of prediction results is conducted against observed data. And a logic tree is introduced to help with epistemic uncertainty and set up different series of source parameters. In addition, a numerical model is used to simulate tsunami propagation and wave height. Under the assumptions of the logic tree and numerical modeling, the relationship between annual probability and maximum tsunami wave height can be obtained. Finally, tsunami hazard maps can be produced and the safety assessment of nuclear power plants can be carried out. The results provide useful information for engineering design and hazard prevention. [ABSTRACT FROM AUTHOR]

For Probabilistic Tsunami Hazard Analysis (PTHA), we propose a logic-tree approach to construct tsunami hazard curves (relationship between tsunami height and probability of exceedance) and present some examples for Japan for the purpose of quantitative assessments of tsunami risk for important coastal facilities. A hazard curve is obtained by integration over the aleatory uncertainties, and numerous hazard curves are obtained for different branches of logic-tree representing epistemic uncertainty. A PTHA consists of a tsunami source model and coastal tsunami height estimation. We developed the logic-tree models for local tsunami sources around Japan and for distant tsunami sources along the South American subduction zones. Logic-trees were made for tsunami source zones, size and frequency of tsunamigenic earthquakes, fault models, and standard error of estimated tsunami heights. Numerical simulation rather than empirical relation was used for estimating the median tsunami heights. Weights of discrete branches that represent alternative hypotheses and interpretations were determined by the questionnaire survey for tsunami and earthquake experts, whereas those representing the error of estimated value were determined on the basis of historical data. Examples of tsunami hazard curves were illustrated for the coastal sites, and uncertainty in the tsunami hazard was displayed by 5-, 16-, 50-, 84- and 95-percentile and mean hazard curves. [ABSTRACT FROM AUTHOR]

Submarine landslides can pose serious tsunami hazard to coastal communities. However, performing a comprehensive landslide tsunami hazard assessment for a given area is in general difficult in view of the large uncertainty associated with tsunamigenic source parameters, which are often only approximately defined, based on estimates of the landslide geometry, slide material properties, and resulting kinematics. Therefore, a Probabilistic Tsunami Hazard Analysis (PTHA) should be performed by considering a large number of cases, which is computationally demanding. Here, we present an efficient model based on solving the linear Mild-Slope Equation with a time-dependent source term representing the seafloor motion. This approach allows carrying out many computations, for a large number of landslide scenarios, in a Monte Carlo (MC) approach framework, at a reduced computational cost compared to other available methods, while still providing physically accurate simulations of most landslide tsunami generation and propagation processes. To further speed-up the MC simulations, a database of elementary solutions is first developed, for many landslide sources of unit amplitude motion over a small seafloor area within the possible landslide footprint. For each unit source, the resulting tsunami elevations are computed and saved at many locations of interest. In the MC simulations, a large number of landslide scenarios are defined by randomly selecting slide parameters within their statistical distributions and each is then simulated for their specific bottom motion using a linear combination of the pre-computed unit sources. Hence, each resulting tsunami is quickly computed at the locations of interest by linear superposition. The paper presents the model validation against two tests cases and describes its novel methodology to perform multiple landslide tsunami scenarios. • A numerical model to simulate many landslide tsunami scenarios is presented. • The linear Mild-Slope Equation in the frequency domain with a forcing term is solved. • An example of application in a Monte Carlo framework is performed. • The model would serve as tool for a Probabilistic Tsunami Hazard Analysis (PTHA). • The model should be coupled to reproduce coastal inundation and run-up. [ABSTRACT FROM AUTHOR]

This paper proposes a novel response surface-based method for probabilistic tsunami hazard assessment (PTHA). Although recent advancements in numerical simulation have enabled the accurate characterization of tsunami hazards, the high computational cost of numerical simulation often prohibits its broad application to probabilistic hazard analysis. The proposed method addresses this challenge by constructing the response surface (RS) of a target output using the results of high-fidelity tsunami simulations. The proposed method quantifies uncertainties in key simulation variables and propagates those uncertainties to the target output through the RS in a computationally efficient Monte Carlo simulation (MCS). We illustrate and validate the proposed method through a case study of the tsunami induced by the 2011 Great East Japan earthquake. The case study focuses on Sendai, Ishinomaki, and Kamaishi in Japan as the target locations. The proposed method estimates coastal tsunami heights while considering uncertainties in the fault slip and rake as well as the modeling error associated with the numerical simulation. The MCS allows us to estimate the probability density functions of the tsunami height at the target locations. The proposed method quantifies the contribution of each source of uncertainty to the overall uncertainty in the target output and thus facilitates engineering decision-making. • A novel method for probabilistic tsunami hazard assessment (PTHA) is proposed. • The method constructs a response surface using high-fidelity numerical simulations. • The method propagates uncertainties in key simulation variables to a target output. • The method enables a computationally efficient Monte Carlo simulation for PTHA. [ABSTRACT FROM AUTHOR]