Suchergebnisse

Due to ongoing climate change, overtopping risk is increasing. In order to have effective countermeasures, it is useful to understand overtopping processes in details. In this study overtopping flow on a dike with gentle and shallow foreshores are investigated using a non-hydrostatic wave-flow model, SWASH (an acronym of Simulating WAves till SHore). The SWASH model in 2DV (i.e., flume like configuration) is first validated using the data of long crested wave cases with second order wave generation in the physical model test conducted. After that it is used to produce overtopping flow in different wave conditions and bathymetries. The results indicated that the overtopping risk is better characterized by the time dependent h (overtopping flow depth) and u (overtopping flow velocity) instead of hmax (maximum overtopping flow depth) and umax (maximum overtopping flow velocity), which led to overestimation of the risk. The time dependent u and h are strongly influenced by the dike configuration, namely by the promenade width and the existence of a vertical wall on the promenade: the simulation shows that the vertical wall induces seaward velocity on the dike which might be an extra risk during extreme events. ; This research was part of the CREST (Climate REsilient CoaST) project (http://www.crestproject.be/en), funded by the Flemish Agency for Innovation by Science and Technology, grant number 150028. Corrado Altomare acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.: 792370. ; Peer Reviewed ; Postprint (published version)

The influence of flow velocity on structural damage induced by tsunami inundation is investigated to improve empirical fragility models considering flow velocity as explanatory hazard variable in addition to inundation depth. The analysis is based on extensive tsunami damage data for the 2011 Tohoku earthquake collected by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government. Multivariate tsunami fragility curves are developed through multinomial logistic regression of un-binned data. This approach facilitates the flexible development of various nested models considering inundation depth alone or inundation depth and velocity altogether. Statistical diagnostic metrics, such as the Bayesian Information Criterion, the Akaike Information Criterion, and the residual deviance, are used to determine which model improves the predictability of tsunami damage. The significance and importance of including flow velocity in the vulnerability models are assessed quantitatively by examining the influence of different spatial resolutions in elevation model and different source models. Then, the effects of coastal topography have been investigated. Numerical results show that flow velocity generally improves the fragility models, particularly for severer structural damage states, and that it is important for sites along the coast where the inundation depth is not extremely high. Coarse digital elevation model and inaccurate source models have influence on the calculated values of flow velocity and thus they affect the accuracy of fragility modeling. Finally, two different fragility models are calibrated for plain-type and ria-type coasts by reflecting differences in hydrodynamic behavior and recorded damage on the structures.

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty.

The influence of flow velocity on structural damage induced by tsunami inundation is investigated to improve empirical fragility models considering flow velocity as explanatory hazard variable in addition to inundation depth. The analysis is based on extensive tsunami damage data for the 2011 Tohoku earthquake collected by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government. Multivariate tsunami fragility curves are developed through multinomial logistic regression of un-binned data. This approach facilitates the flexible development of various nested models considering inundation depth alone or inundation depth and velocity altogether. Statistical diagnostic metrics, such as the Bayesian Information Criterion, the Akaike Information Criterion, and the residual deviance, are used to determine which model improves the predictability of tsunami damage. The significance and importance of including flow velocity in the vulnerability models are assessed quantitatively by examining the influence of different spatial resolutions in elevation model and different source models. Then, the effects of coastal topography have been investigated. Numerical results show that flow velocity generally improves the fragility models, particularly for severer structural damage states, and that it is important for sites along the coast where the inundation depth is not extremely high. Coarse digital elevation model and inaccurate source models have influence on the calculated values of flow velocity and thus they affect the accuracy of fragility modeling. Finally, two different fragility models are calibrated for plain-type and ria-type coasts by reflecting differences in hydrodynamic behavior and recorded damage on the structures.

In this study, earthquake rupture models for future mega-thrust earthquakes in the Nankai–Tonankai subduction zone are developed by incorporating the main characteristics of inverted source models of the 2011 Tohoku earthquake. These scenario ruptures also account for key features of the national tsunami source model for the Nankai–Tonankai earthquake by the Central Disaster Management Council of the Japanese Government. The source models capture a wide range of realistic slip distributions and kinematic rupture processes, reflecting the current best understanding of what may happen due to a future mega-earthquake in the Nankai–Tonankai Trough, and therefore are useful for conducting probabilistic tsunami hazard and risk analysis. A large suite of scenario rupture models is then used to investigate the variability of tsunami effects in coastal areas, such as offshore tsunami wave heights and onshore inundation depths, due to realistic variations in source characteristics. Such investigations are particularly valuable for tsunami hazard mapping and evacuation planning in municipalities along the Nankai–Tonankai coast.

In this study, earthquake rupture models for future mega-thrust earthquakes in the Nankai-Tonankai subduction zone are developed by incorporating the main characteristics of inverted source models of the 2011 Tohoku earthquake. These scenario ruptures also account for key features of the national tsunami source model for the Nankai-Tonankai earthquake by the Central Disaster Management Council of the Japanese Government. The source models capture a wide range of realistic slip distributions and kinematic rupture processes, reflecting the current best understanding of what may happen due to a future mega-earthquake in the Nankai-Tonankai Trough, and therefore are useful for conducting probabilistic tsunami hazard and risk analysis. A large suite of scenario rupture models is then used to investigate the variability of tsunami effects in coastal areas, such as off-shore tsunami wave heights and on-shore inundation depths, due to realistic variations in source characteristics. Such investigations are particularly valuable for tsunami hazard mapping and evacuation planning in municipalities along the Nankai-Tonankai coast.

Developing an effective tsunami evacuation plan is essential for disaster risk reduction in coastal regions. To develop effective tsunami evacuation plans, real transportation network, interaction among evacuees, and uncertainties associated with future tsunami events need to be considered in a holistic manner. This study aims to develop such an integrated tsunami evacuation approach using agent-based evacuation simulation and advanced stochastic tsunami hazard assessment. As a case study, a urban area in Padang, Indonesia, threatened by tsunamis from the Mentawai–Sunda subduction zone, is adopted. The uncertainty of the tsunami hazard is taken into account by generating 900 stochastic tsunami inundation maps for three earthquake magnitudes, i.e. 8.5, 8.75, and 9.0. A simplified evacuation approach considering the evacuees moving directly to evacuation areas (defined a priori) is compared with two more rigorous agent-based modeling approaches: (a) a two-destination-point tsunami evacuation plan developed by the local government and (b) a multiple-destination-point plan developed in this study. The improved agent-based stochastic tsunami evacuation framework with multiple destinations takes advantage of the extensive tsunami hazard analyses to define safe areas in a dynamic manner and is capable of capturing the uncertainty of future tsunami risk in coastal areas. In contrast, the results clearly show that the simplified approach significantly underestimates the evacuation time, and the existing tsunami evacuation routes identified by local authorities may be insufficient to save lives.

Abstract. Nankai–Tonankai megathrust earthquakes and tsunamis pose significant risks to coastal communities in western and central Japan. Historically, this seismic region hosted many major earthquakes, and the current national tsunami hazard assessments in Japan consider megathrust events as those having moment magnitudes between 9.0 and 9.1. In responding to the lack of rigorous uncertainty analysis, this study presents an extensive tsunami hazard assessment for the Nankai–Tonankai Trough events, focusing on the southwestern Pacific region of Japan. A set of 1000 kinematic earthquake rupture models is generated via stochastic source modelling approaches, and Monte Carlo tsunami simulations are carried out by considering high-resolution grid data of 10 m and coastal defence structures. Significant advantages of the stochastic tsunami simulation methods include the enhanced capabilities to quantify the uncertainty associated with tsunami hazard assessments and to effectively visualize the results in an integrated manner. The results from the stochastic tsunami simulations can inform regional and local tsunami risk reduction actions in light of inevitable uncertainty associated with such tsunami hazard assessments and complement conventional deterministic tsunami scenarios and their hazard predictions, such as those developed by the Central Disaster Management Council of the Japanese Cabinet Office.