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In this study, we develop a single-phase free-surface flow model with the improved lattice kinetic scheme (LKS) and the volume of fluid (VOF) method. We implement the piecewise linear interface calculation (PLIC) algorithm to reconstruct the interface. The gas phase velocity is extrapolated from the liquid phase velocity using a velocity extension method and the signed distance function (SDF) to advect the VOF function. We calculate the SDF with the level-set reinitialisation method, and the VOF function is used as the initial profile. We discuss the advantages of the improved LKS in terms of the free-surface boundary condition by means of distribution functions, which conflict in interface cells in conventional streaming and collision processes in the lattice Boltzmann method (LBM). The proposed free-surface model is verified with well-known advection benchmark problems. We also simulate a static water problem and dam break flow. The proposed model accurately calculates the dam break surge front. Although the surge front position depends on the spatial resolution in the conventional LBM free-surface model, the improved LKS results are approximately the same regardless of the resolution. This is a critical difference between the proposed and conventional LBM models and represents a unique feature of the improved LKS. • A single-phase free-surface flow model by the improved LKS is developed. • Conflicts of the distribution function do not arise because the boundary conditions are given as the macroscopic variables. • The velocity field is extended by the SDF and the advection of the VOF function is calculated by the PLIC approach. • The proposed model is stable without the turbulence model and agrees well with the experimental results. [ABSTRACT FROM AUTHOR]

Free-surface flow problems occur in numerous disaster simulations, such as tsunami inland penetration in urban areas. Simulation models for these problems must be non-hydrostatic, three-dimensional and highly resolved because of the strong non-linearity and higher-order physical phenomena. However, three-dimensional large-scale tsunami simulations based on conventional computational fluid dynamics (CFD) solving the Navier-Stokes equations are challenging due to the pressure Poisson equation in incompressible Navier-Stokes fluid modeling. The lattice Boltzmann method (LBM) is an alternative simulation tool that is attracting attention as a fully explicit and efficient approach. The LBM does not have to iteratively solve the pressure Poisson equation and is therefore considered to have an advantage over other methods when executing high-performance three-dimensional tsunami simulations. In the current study, we developed a fully explicit free-surface model using the LBM in which the more advanced multiple-relaxation-time (MRT) collision model is used, along with the piecewise linear interface calculation (PLIC) approach. Through classic dam-break problems, we validated the appropriate parameter settings, including the weak compressibility, for tsunami simulations. The benchmark tests showed that our model accurately simulates the three-dimensional dam-break flows and controls the compressibility drop in the second-order value of the Mach number. [ABSTRACT FROM AUTHOR]

The devastating consequences of tsunamis on coastal infrastructure have highlighted the urgent need for effective disaster risk reduction strategies. To mitigate tsunami disasters, the insurance industry plays a vital role in implementing risk transfer measures by providing financial protection against asset damage. However, the current research on catastrophe insurance policies for coastal infrastructure lacks consideration of climate change effects. It is essential to take into account the non-stationary effects of sea-level rise to develop long-term tsunami disaster mitigation measures and promote socioeconomic resilience in coastal communities. This paper aims to provide an insurance portfolio optimization framework for coastal residential buildings subjected to tsunamis considering non-stationary sea-level rise effects based on a stochastic simulation approach. A spatiotemporal probabilistic sea-level rise hazard assessment is carried out by utilizing available climate models and considering several emission scenarios. Tsunami propagation analyses under various sea-level rise cases are performed to evaluate the time-variant tsunami hazard curves based on Monte Carlo simulation. A life cycle-based stochastic insurance claim model associated with the cumulative loss of building assets is developed based on a non-stationary compound renewal process. Finally, a sample average approximation method is leveraged to estimate the optimum basic insurance premium rate by maximizing the insurer's profit under a cost-constrained insurance purchase decision of homeowners. As a case study, the proposed framework is applied to multiple municipalities situated in the tsunami-prone region of Kochi Prefecture, Japan. Sea-level rise substantially decreases the maximum profits of tsunami insurers and increases the premium rate and ruin probability. [ABSTRACT FROM AUTHOR]

The numerical solution to the conservative Allen–Cahn (AC) equation obtained by the lattice Boltzmann method (LBM) is problematic due to the creation of an unphysical phase in the bulk region. In this study, we propose an approach to suppress this unexpected behaviour by filtering the phase-field function. In the AC equation simulations, the phase-field function typically oscillates in the bulk region and overshoots or undershoots near the interface. The aim of the filtering approach is to create a smooth interface profile through several filtering iterations and improve the calculation accuracy of the interfacial normal. We demonstrate that the filtering process effectively suppresses the creation of an unphysical phase through Zalesak's disc rotation and single vortex tests. The filtering process improves the accuracy of the calculated interface tension under the same thickness for a stationary droplet benchmark test. A comparative study with the Cahn-Hilliard (CH) equation is conducted for a single rising bubble flow. The characteristics of both equations are discussed. Furthermore, the filtered conservative AC equation is found to preserve the shape of the rising bubble well. [Display omitted] • A filtering approach is proposed to the LBM for the conservative Allen–Cahn equation. • The filtering effectively prevents the creation of the unphysical phase in the bulk region. • The effect of thickness on the diffusion of the phase-field function is studied. • The filtering improves the calculation accuracy of the interface tension. • A comparison with the Cahn-Hilliard equation is conducted for the rising bubble flow. [ABSTRACT FROM AUTHOR]

As confirmed by the extreme tsunami events over the last decade (the 2004 Indian Ocean, 2010 Chile and 2011 Japan tsunami events), mitigation measures and effective evacuation planning are needed to reduce disaster risks. Modeling tsunami evacuations is an alternative means to analyze evacuation plans and possible scenarios of evacuees' behaviors. In this paper, practical applications of an agent-based tsunami evacuation model are presented to demonstrate the contributions that agent-based modeling has added to tsunami evacuation simulations and tsunami mitigation efforts. A brief review of previous agent-based evacuation models in the literature is given to highlight recent progress in agent-based methods. Finally, challenges are noted for bridging gaps between geoscience and social science within the agent-based approach for modeling tsunami evacuations. [ABSTRACT FROM AUTHOR]

Although the 2004 Indian Ocean tsunami occurred several years ago and all the building repair and infrastructure reconstruction needed in Thailand to repair the damage caused by the tsunami are complete, there is still a need for damage assessment methods that can be used in future tsunami damage assessments in Thailand and that can possibly be applied to other countries. This study summarizes three methods for assessing tsunami damage, "tsunami damage criteria," "tsunami damage ratios" and "tsunami fragility curves," based on damage data from the 2004 Indian Ocean tsunami in Thailand, and these methods are compared using other tsunami events. Using the data from a field survey of damaged buildings, tsunami damage criteria were summarized for each degree of damage as a function of inundation depth for different building types. Tsunami damage ratios were summarized using building damage data obtained from surveys in the field and reconstruction cost estimates provided by the Thai government. The fragility curves developed were validated based on building performance data obtained from full-scale experiments on buildings and columns. Despite differences in the tsunami characteristics (inundation depth, current velocity and hydrodynamic force), the damage probabilities were nearly the same. The summarized methods might be useful for future tsunami damage assessments and loss estimation in Thailand and serve as guidelines for tsunami damage assessment in other countries. [ABSTRACT FROM AUTHOR]

When a large-scale flood disaster occurs, it is important to identify the flood areas in a short time in order to effectively support the affected areas afterwards. Synthetic Aperture Radar (SAR) is promising for flood detection. A number of change detection methods have been proposed to detect flooded areas with pre- and post-event SAR data. However, it remains difficult to detect flooded areas in built-up areas due to the complicated scattering of microwaves. To solve this issue, in this paper we propose the idea of analyzing the local changes in pre- and post-event SAR data as well as the larger-scale changes, which may improve accuracy for detecting floods in built-up areas. Therefore, we aimed at evaluating the effectiveness of multi-scale SAR analysis for flood detection in built-up areas using ALOS-2/PALSAR-2 data. First, several features were determined by calculating standard deviation images, difference images, and correlation coefficient images with several sizes of kernels. Then, segmentation on both small and large scales was applied to the correlation coefficient image and calculated explanatory variables with the features at each segment. Finally, machine learning models were tested for their flood detection performance in built-up areas by comparing a small-scale approach and multi-scale approach. Ten-fold cross-validation was used to validate the model, showing that highest accuracy was offered by the AdaBoost model, which improved the F1 Score from 0.89 in the small-scale analysis to 0.98 in the multi-scale analysis. The main contribution of this manuscript is that, from our results, it can be inferred that multi-scale analysis shows better performance in the quantitative detection of floods in built-up areas. [ABSTRACT FROM AUTHOR]

SUMMARY Characteristics of the tsunami decay processes are examined following the definition and discussion of the major terms involved: 'moving root mean squared amplitude', 'tsunami coda' and 'non-dimensional tsunami amplitude' (NDA). Tsunami waveform data observed at tidal stations in Japan during two Kuril Island earthquake tsunamis in 2006 and 2007 are analysed. The tsunami codas of these events showed the following characteristics. (1) The decay process determined by the tsunami coda of the 2006 tsunami implies that the decay time constant at a tidal station depends on which ocean the station is facing. (2) Fluctuations of the NDAs in the tsunami codas are stochastically approximated by either the Rayleigh distribution or the normal distribution and the distributions of the NDAs at most tidal stations are similar. (3) Differences in the decay processes between these two tsunami events were small with regard to the averaged decay time constants and the distributions of the NDAs. These findings may be the first step towards improved forecasting of the tsunami decay process. [ABSTRACT FROM AUTHOR]

On March 11th, 2011, the Pacific coast of Japan was hit by a tsunami generated by the largest earthquake (M9.0) in the history of the country and causing a wide range of devastating damage. Using preliminary reported data from many sources, some topics such as tsunami fatality ratio and tsunami fragility curves for structural damage are discussed and compared with other countries. This paper aims to discuss the damage characteristics of this tsunami as well as its mechanism, as observed through field surveys conducted over the 4 months following the tsunami. The field survey covers 13 areas in the Miyagi prefecture from Kesennuma city in the northernmost region to Yamamoto town in the southernmost region. The arrival time of the first tsunami along the coastal areas in the Miyagi prefecture was confirmed by stopped clocks found during the survey. The damage mechanism of coastal structures such as breakwaters, seawalls, tsunami gates, and evacuation buildings was investigated and discussed. Damage characteristics for each area, i.e., urban areas, port, coastal structures, fisheries, and agricultural areas, were also summarized. The conclusions drawn from the data analysis suggest that experience and education (soft countermeasures) are important to reduce the loss of life, as shown for example in the Sanriku area. The field surveys indicate that wood and reinforced-concrete (RC) structures should be balanced to survive both earthquake and tsunami forces, and the structural design for buildings should be reconsidered after the example in Onagawa town. In addition, coastal structures for tsunami countermeasures (hard countermeasures) should be more properly designed for survival instead of becoming floating debris upon being overturned by a tsunami. The combination of both hard and soft measures is especially necessary for optimizing the outcomes following a great disaster. These recommendations should be taken into consideration in the reconstruction efforts for better tsunami countermeasures in the future. [ABSTRACT FROM AUTHOR]

The authors visually inspected the building damage caused by the 2011 Tohoku earthquake tsunami, using the pre and post-event aerial photos. First, we prepared the mosaic of post-tsunami aerial photos acquired by Geospatial Information Authority of Japan (GSI), and conducted the visual inspection of buildings damage to classify the damage. The damage classification results are compiled with building shape files on GIS for mapping the structural vulnerability in the tsunami inundation zone. Finally, we discussed the structural vulnerability in the tsunami affected area based on mapping results of building damage. [ABSTRACT FROM AUTHOR]

Fragility functions, as new measures for estimating structural damage and casualties due to tsunami attack, are developed by an integrated approach using numerical modeling of tsunami inundation and GIS analysis of post-tsunami survey data of the 2004 Sumatra–Andaman earthquake tsunami disaster, obtained from Banda Aceh, Indonesia. The fragility functions are expressed as the damage probabilities of structures or death ratio with regard to the hydrodynamic features of tsunami inundation flow, such as inundation depth, current velocity and hydrodynamic force. They lead to the new understandings of the relationship between local vulnerability and tsunami hazard in a quantitative manner. [ABSTRACT FROM AUTHOR]

Abstract: Using an integrated approach including satellite imagery analysis, field measurements, and numerical modeling, we investigated the damage to mangroves caused by the 2004 Indian Ocean tsunami at Pakarang Cape in Pang Nga Province, Thailand. Comparing pre- and post-tsunami satellite imagery of the study area, we found that approximately 70% of the mangrove forest was destroyed by the tsunami. Based on field observations, we found that the survival rate of mangroves increased with increasing stem diameter. Specifically, we found that 72% of Rhizophora trees with a 25–30cm stem diameter survived the tsunami impact, whereas only 19% with a 15–20cm stem diameter survived. We simulated the 2004 Indian Ocean tsunami using the nonlinear shallow-water wave theory to reproduce the tsunami inundation flow and investigated the bending moment acting on the mangrove trees. Results of the numerical model showed that the tsunami inundated areas along the mangrove creeks, and its current velocity reached 5.0ms−1. Based on the field measurements and numerical results, we proposed a fragility function for mangroves, which is the relationship between the probability of damage and the bending stress caused by the maximum bending moment. We refined the numerical model to include the damage probability of mangrove forests using the obtained fragility function to investigate the tsunami reduction effect of mangrove forest. Under simple numerical conditions related to the mangrove forest, ground level, and incident wave, the model showed that a mangrove forest of Rhizophora sp. with a density of 0.2treesm−2 and a stem diameter of 15cm in a 400m wide area can reduce the tsunami inundation depth by 30% when the incident wave is assumed to have a 3.0m inundation depth and a wave period of 30min at the shoreline. However, 50% of the mangrove forest is destroyed by a 4.5m tsunami inundation depth, and most of the mangrove forest is destroyed by a tsunami inundation depth greater than 6m. The reduction effect of tsunami inundation depth decreased when the tsunami inundation depth exceeded 3m, and was mostly lost when the tsunami inundation depth exceeded 6m. [Copyright &y& Elsevier]

A new analytical solution of tsunami which is obliquely incident on a continental slope is derived based on the linear shallow water wave theory. The model of a continental slope consists of a finite constant slope and a bottom of uniform depth and has a vertical wall at the shoreline. Because of the existence of the vertical wall, another function can be taken as one of the fundamental solutions on a slope in addition to the confluent hypergeometric function M. Based on the solution obtained, the characteristics of tsunami amplification on a continental slope are discussed in terms of the conditions of the incidence. The magnitude of the amplification can be predicted with several parameters of wave incidence, such as, the incident angle and the relative incident-wave length to the topography. Especially, when a tsunami is incident almost parallel to the slope, we found that there exists distinctive amplifications for particular parameters characterizing the incident wave. The effect of the existence of the vertical wall is also discussed. The characteristics of amplification also depend much on the position of the vertical wall. [ABSTRACT FROM AUTHOR]

Fundamental characteristics of tsunamis propagating over an oceanic ridge are investigated analytically based on the linear shallow water wave theory. The oceanic ridge model used has a triangular shape which is formed by the combination of a constant slope and a bottom of uniform depth. Wave pattern of on-ridge tsunamis varies depending on the obliquity of incident waves. Especially, standing waves are formed when the incident wave angle to the ridge exceeds the critical angle. Then no transmitted waves exist because of the evanescent waves. The present study is applied to the 1996 Irian Jaya tsunami which propagated over the South-Honshu ridge. The characteristics of on-ridge tsunamis observed at Chichijima and Hachijojima, which are close to the South-Honshu ridge, can be partly explained by using the solution derived in the present study. [ABSTRACT FROM AUTHOR]

Tsunamis are rare events compared with the other natural disasters, but once it happens, it can be extremely devastating to the coastal communities. Extensive inland penetration of tsunamis may cause the difficulties of understanding its impact in the aftermath of its generation. Therefore the social needs to technologies of detecting the wide impact of great tsunamis have been increased. Recent advances of remote sensing and technologies of image analysis meet the above needs and lead to more rapid and efficient understanding of tsunami affected areas. This paper provides a review of how remote sensing methods have developed to contribute to post-tsunami disaster response. The evaluations in the performances of the remote sensing methods are discussed according to the needs of tsunami disaster response with future perspective. [ABSTRACT FROM AUTHOR]

In this study, we present an optimization method for determining a cost‐effective sparse configuration for tsunami gauges to realize the reconstruction of high‐resolution wave height distribution throughout the target region based on the concept of super‐resolution. This optimization method consists of three procedures. First, we generate time series data of tsunami wave heights at synthetic gauges by conducting numerical simulations of various earthquake and tsunami scenarios at the target site. Next, we apply proper orthogonal decomposition to the synthetic tsunami data to extract the spatial features of the wave height distribution. Finally, according to these spatial features, an optimization process is performed to determine a sparse configuration of synthetic gauges. In the optimization, the optimal gauges are sequentially selected from the set of synthetic gauges to reconstruct the wave height distribution with the highest accuracy. Targeting hypothetical Nankai Trough earthquakes and tsunamis, we determine the optimal configuration near Shikoku and demonstrate the wave height reconstruction capability of the approach by comparing the performance of networks with optimally and randomly placed gauges. The results indicate that coastal gauges contribute more to improving the reconstruction accuracy and that a configuration with 21 optimal gauges has satisfactory performance. In addition, we assess the performance of the existing NOWPHAS network installed in the Shikoku region and find that the reconstruction performance of the existing network is equivalent to that of the optimal gauge network. Plain Language Summary: This study introduces a method of optimizing the sparse locations where actual tsunami gauges should be installed to obtain information on tsunami wave heights at any given point. By optimizing the locations of the observation points, it is possible to extend observations recorded at only a small number of points to obtain a good approximation to data at other points where the tsunami was not directly observed. First, numerical simulations are performed based on assumed earthquake and tsunami scenarios to generate synthetic time series data of tsunami waves. Then, by applying proper orthogonal decomposition to the obtained synthetic data, the characteristics of the tsunami wave height distribution are extracted. Finally, these characteristics are used to perform optimization by sequentially selecting the best gauges from among a set of candidate points to reconstruct wave height information for the entire target area, thereby determining the placements of a limited number of gauges. In a numerical demonstration example simulating a Nankai Trough earthquake and tsunami, the placement of gauges off the coast of Shikoku is optimized, and it is shown that the wave heights at arbitrary points over the entire area can be reproduced using data from at least 21 optimally placed gauges. Key Points: An optimization method implementing a greedy algorithm is presented to design a cost‐effective observational network of tsunami gaugesHigh‐resolution information about tsunami wave height is constructed from sparse observations based on the concept of super‐resolutionThe optimization process considering the existing observation network locations identifies their sufficiency or deficiency [ABSTRACT FROM AUTHOR]

On 28 September 2018, a large earthquake of magnitude 7.5 occurred at 72 km away from the city of Palu, Central Sulawesi, Indonesia. Following the main shock, a series of tsunami attacked the eastern coasts of central Sulawesi and the severe damages were reported along the coast of Palu Bay.In the aftermath of the event, since the rupture was occurred along Palu-Koro strike-slip fault, the tsunami impact was expected to be relatively low compared with the other past tsunami events caused by the thrust fault rupture. However, the reported damage, more than 70,000 houses were reported to be damaged, was much more severe than expected because of the combination of strong ground motion, landslides, mudflows and tsunamis.After the event occurred, as a part of the Indonesian government's reconnaissance, we conducted a post-tsunami field survey to identify the tsunami impact. The survey was conducted on 21 and 22 October, 2018, and aimed to measure the extent of tsunami inland penetration with RTK-GPS, flow depths and to inspect the structural damage. The survey also aimed to collect the ground truth information for satellite remote sensing and survivor video analysis to understand how the tsunami attacked and devastated the coastal areas of central Palu.From the survey at the central Palu, we found that the major tsunami impact was concentrated within about 200 m inland from the shoreline. The spatial distribution of tsunami flow depths was scattered in the narrow range of tsunami inundation zone of the central Palu coast; 1-3m flow depths in average, 6 m the maximum at the central Palu.Some survivor videos provided important information on tsunami attack, especially on the time series of the first and second tsunami attacks. From the video analysis, we found that the second tsunami hit Palu Grand Mall with the splash height of almost 8 m above the sea level, and the difference of 1st. and 2nd. tsunami attack was likely to be 2 minutes. This implies that these tsunamis were generated by a phenomenon with short time scale or different sources. [ABSTRACT FROM AUTHOR]

Tsunami fragility functions (TFF) are statistical models that relate a tsunami intensity measure to a given building damage state, expressed as cumulative probability. Advances in computational and data retrieval speeds, coupled with novel deep learning applications to disaster science, have shifted research focus away from statistical estimators. TFFs offer a "disaster signature" with comparative value, though these models are seldom applied to generate damage estimates. With applicability in mind, we challenge this notion and investigate a portion of TFF literature, selecting three TFFs and two application methodologies to generate a building damage estimation baseline. Further, we propose a simple machine learning method, trained on physical parameters inspired by, but expanded beyond, TFF intensity measures. We test these three methods on the 2011 Ishinomaki dataset after the Great East Japan Earthquake and Tsunami in both binary and multi-class cases. We explore: (1) the quality of building damage estimation using TFF application methods; (2) whether TFF can generalize to out-of-domain building damage datasets; (3) a novel machine learning approach to perform the same task. Our findings suggest that: both TFF methods and our model have the potential to achieve good binary results; TFF methods struggle with multiple classes and out-of-domain tasks, while our proposed method appears to generalize better. [ABSTRACT FROM AUTHOR]

We revisited the lessons of the 2011 Great East Japan Earthquake Tsunami disaster specifically on the response and impact, and discussed the paradigm shift of Japan's tsunami disaster management policies and the perspectives for reconstruction. Revisiting the modern histories of Tohoku tsunami disasters and pre-2011 tsunami countermeasures, we clarified how Japan's coastal communities have prepared for tsunamis. The discussion mainly focuses on structural measures such as seawalls and breakwaters and non-structural measures of hazard map and evacuation. The responses to the 2011 event are discussed specifically on the tsunami warning system and efforts to identify the tsunami impacts. The nation-wide post-tsunami survey results shed light on the mechanisms of structural destruction, tsunami loads and structural vulnerability to inform structural rehabilitation measures and land-use planning. Remarkable paradigm shifts in designing coastal protection and disaster mitigation measures were introduced, leading with a new concept of potential tsunami levels: Prevention (Level 1) and Mitigation (Level 2) levels according to the level of 'protection'. The seawall is designed with reference to Level 1 tsunami scenario, while comprehensive disaster management measures should refer to Level 2 tsunami for protection of human lives and reducing potential losses and damage. Throughout the case study in Sendai city, the proposed reconstruction plan was evaluated from the tsunami engineering point of view to discuss how the post 2011 paradigm was implemented in coastal communities for future disaster mitigation. The analysis revealed that Sendai city's multiple protection measures for Level 2 tsunami will contribute to a substantial reduction of the tsunami inundation zone and potential losses, combined with an effective tsunami evacuation plan. [ABSTRACT FROM AUTHOR]

ABSTRACT Udo, K.; Takeda, Y., and Koshimura, S., 2018. Detection of coastal damage using differences in automatically generated digital surface models (DSMs): Application to the 2011 Off the Pacific Coast of Tohoku Earthquake Tsunami. 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. 696–700. Coconut Creek (Florida), ISSN 0749-0208. The detection of coastal damage due to the 2011 Off the Pacific Coast of Tohoku Earthquake Tsunami on the southern Sendai Coast was attempted via state-of-the-art remote sensing technology using ALOS PRISM satellite images with a spatial resolution of 2.5 m. Digital surface models (DSMs) were generated semi-automatically, and their accuracies were confirmed via comparisons with digital elevation models generated from aerial laser measurements. The differences between the DSMs prior to and after the tsunami were analyzed statistically for each type of land cover: residential districts, rice fields, coastal forests, and beaches. It was demonstrated that the damage to the coastal forests and residential districts could be detected though the damage in the low land area was difficult to be detected because of its small undulations in topography. Low pass filtering was employed to remove the jitter noise; however, the major characteristics such as damage in the coastal forests and residential areas were not changed by the filtering; that is, the major statistical characteristics could be detected without filtering. [ABSTRACT FROM AUTHOR]

Udo, K.; Takeda, Y., and Koshimura, S., 2018. Detection of coastal damage using differences in automatically generated digital surface models (DSMs): Application to the 2011 Off the Pacific Coast of Tohoku Earthquake Tsunami. 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. 696–700. Coconut Creek (Florida), ISSN 0749-0208. The detection of coastal damage due to the 2011 Off the Pacific Coast of Tohoku Earthquake Tsunami on the southern Sendai Coast was attempted via state-of-the-art remote sensing technology using ALOS PRISM satellite images with a spatial resolution of 2.5 m. Digital surface models (DSMs) were generated semi-automatically, and their accuracies were confirmed via comparisons with digital elevation models generated from aerial laser measurements. The differences between the DSMs prior to and after the tsunami were analyzed statistically for each type of land cover: residential districts, rice fields, coastal forests, and beaches. It was demonstrated that the damage to the coastal forests and residential districts could be detected though the damage in the low land area was difficult to be detected because of its small undulations in topography. Low pass filtering was employed to remove the jitter noise; however, the major characteristics such as damage in the coastal forests and residential areas were not changed by the filtering; that is, the major statistical characteristics could be detected without filtering. [ABSTRACT FROM AUTHOR]

On September 8, 2017 (UTC), a normal-fault earthquake occurred 87 km off the southeast coast of Mexico. This earthquake generated a tsunami that was recorded at coastal tide gauge and offshore buoy stations. First, we conducted a numerical tsunami simulation using a single-fault model to understand the tsunami characteristics near the rupture area, focusing on the nearby tide gauge stations. Second, the tsunami source of this event was estimated from inversion of tsunami waveforms recorded at six coastal stations and three buoys located in the deep ocean. Using the aftershock distribution within 1 day following the main shock, the fault plane orientation had a northeast dip direction (strike $$= 320^{\circ }$$ , dip $$= 77^{\circ }$$ , and rake $$=-92^{\circ }$$ ). The results of the tsunami waveform inversion revealed that the fault area was 240 km × 90 km in size with most of the largest slip occurring on the middle and deepest segments of the fault. The maximum slip was 6.03 m from a 30 × 30 km segment that was 64.82 km deep at the center of the fault area. The estimated slip distribution showed that the main asperity was at the center of the fault area. The second asperity with an average slip of 5.5 m was found on the northwest-most segments. The estimated slip distribution yielded a seismic moment of $$2.9 \times 10^{21}$$ Nm (Mw = 8.24), which was calculated assuming an average rigidity of $$7\times 10^{10}$$ N/m. [ABSTRACT FROM AUTHOR]

A powerful tsunami triggered by the Mw 9.0 Tohoku earthquake struck the northern Pacific coast of Japan in 2011, destroying several coastal communities in Iwate Prefecture, Miyagi Prefecture, and Fukushima Prefecture. Here, we investigate a new spatio-temporal slip model (model B) developed by the Cabinet Office of the Government of Japan. This slip model was compared against the non-uniform slip model estimated using tsunami waveform data (model A). We focused our analysis on two areas that were destroyed by the tsunami. The town of Onagawa and the coastal Sendai Plain area were selected because they were located in front of the epicentre, where the most significant slips were registered. Our simulation results revealed that the spatio-temporal slip distribution better replicated the observed data. Regarding the tsunami waveforms from the coastal tide gauge station and offshore stations, the Cabinet Office's slip model showed an approximately 30% better accuracy relative to the non-uniform slip model. Furthermore, by comparing the local inundation features at two locations with unique topographic and coastal morphological characteristics, we also found that model B better replicated the measured inundation depths. Finally, considering that tsunami-induced damage is a direct function of various inundation features such as the flow depth and flow velocity, this new slip model can generate more realistic damage scenarios for future tsunami assessments. [ABSTRACT FROM AUTHOR]

The lattice Boltzmann method (LBM) has recently attracted attention as a simple computational fluid dynamics (CFD) method that does not directly solve macroscopic equations. Due to the advantage of its local scheme, the LBM is expected to efficiently achieve highly accurate and high-resolution fluid simulations. In particular, the application of the LBM to disaster simulations has been studied since the proposal of the LBM for nonlinear shallow water equations (LABSWE). However, it is well known that the LBM is prone to computational instability in high Reynolds number flows. A tsunami inundating an urban area is considered a high Reynolds number flow because of its violent flow. The numerical stability in such flows must be enhanced for the application of the LBM to real-world tsunami simulations. For this purpose, it is practical to introduce the subgrid-scale (SGS) model into the multiple-relaxation-time (MRT) model. Notably, the MRT model is computationally more expensive than the conventional lattice Bhatnagar–Gross–Krook (BGK) model. In this study, we modified the SGS model for the MRT model. We verified the calculation accuracy by focusing on grid size differences in the classical benchmark problems in high Reynolds number flows. Finally, we simulated the 2011 tsunami off the Pacific coast caused by the Tohoku earthquake. The LBM simulations reproduced the tsunami propagation waveform and inundation depth with the computational accuracy equally as good as that of the finite difference method (FDM). • The tsunami by the 2011 Great East Japan Earthquake is simulated. • The proposed model is stable in the high Reynolds number flows. • A comparative study with the finite difference method is demonstrated. [ABSTRACT FROM AUTHOR]

The tsunami caused by the Tonga submarine volcanic eruption that occurred at 13:15 Japan Time (JST) on January 15, 2022, exposed a blind spot in Japan's tsunami monitoring and warning system, which was established in 1952 for local tsunamis and expanded to distant tsunamis after the 1960 Chile tsunami. This paper summarizes how the warning system responded to the unprecedented tsunami, the actual evacuation process, and the damage it caused in Japan. Initially, the tsunami from the volcanic eruption was expected to arrive at approximately midnight with amplitudes of less than 20 cm. However, a series of short waves arrived at approximately 21:00, a few hours earlier than expected. The early arrival of these sea waves coincided with a rapid increase in atmospheric pressure; then, the short-period component was predominant, and the wave height was amplified while forming wave groups. After a 1.2 m tsunami was observed in Amami City in southern Japan at 23:55 JST, the Japan Meteorological Agency issued a tsunami warning/advisory. The tsunami continued, and all advisories were cleared at 14:00 JST on January 16. Information about this tsunami and the response to it are summarized here, including the characteristics and issues of the actual tsunami evacuation situation in each region. There were no casualties, but the issues that emerged included difficulty evacuating on a winter night and traffic congestion due to evacuation by car and under the conditions of the COVID-19 pandemic. In the coastal area, damage to fishing boats and aquaculture facilities was reported due to the flow of the tsunami. In addition, damage to aquaculture facilities, including those producing oysters, scallops, seaweed and other marine products, decreased the supply of marine products, and the economic impact is likely to increase in the future. [ABSTRACT FROM AUTHOR]

This study proposes a new method for the uncertainty estimation of coseismic slip distribution on the plate interface deduced from real-time global navigation satellite system (GNSS) data and explores its application for tsunami inundation prediction. Jointly developed by the Geospatial Information Authority of Japan and Tohoku University, REGARD (REal-time GEONET Analysis system for Rapid Deformation monitoring) estimates coseismic fault models (a single rectangular fault model and slip distribution model) in real time to support tsunami prediction. The estimated results are adopted as part of the Disaster Information System, which is used by the Cabinet Office of the Government of Japan to assess tsunami inundation and damage. However, the REGARD system currently struggles to estimate the quantitative uncertainty of the estimated result, although the obtained result should contain both observation and modeling errors caused by the model settings. Understanding such quantitative uncertainties based on the input data is essential for utilizing this resource for disaster response. We developed an algorithm that estimates the coseismic slip distribution and its uncertainties using Markov chain Monte Carlo methods. We focused on the Nankai Trough of southwest Japan, where megathrust earthquakes have repeatedly occurred, and used simulation data to assume a Hoei-type earthquake. We divided the 2951 rectangular subfaults on the plate interface and designed a multistage sampling flow with stepwise perturbation groups. As a result, we successfully estimated the slip distribution and its uncertainty at the 95% confidence interval of the posterior probability density function. Furthermore, we developed a new visualization procedure that shows the risk of tsunami inundation and the probability on a map. Under the algorithm, we regarded the Markov chain Monte Carlo samples as individual fault models and clustered them using the k-means approach to obtain different tsunami source scenarios. We then calculated the parallel tsunami inundations and integrated the results on the map. This map, which expresses the uncertainties of tsunami inundation caused by uncertainties in the coseismic fault estimation, offers quantitative and real time insights into possible worst-case scenarios. [ABSTRACT FROM AUTHOR]

Assessing the hazard and damage of a potential tsunami is an ongoing challenge in tsunami research. This study begins by simulating tsunami hazards using historical events. A tsunami propagation model is used to obtain the estimated maximum tsunami height along the west coast of Thailand for a rough return period, and rupture locations that have the potential to generate catastrophic tsunamis in Thailand for a specific return period are proposed. A tsunami inundation model is then performed to quantify each building's maximum inundation depth, using high-resolution satellite images to extract each building's location for the areas of interest located in southern Thailand. Nam Khem village and Patong beach are selected as study areas to represent village communities and tourist attractions, respectively. The model results are then used to obtain the numbers of exposed inhabitants and buildings for each earthquake return period. The developed tsunami fragility curves are applied to these figures to determine the number of potentially damaged buildings. The analysis suggests that the propagation model can be used to obtain rough estimations because it provided results similar to those of the inundation model. However, material type must be considered when fragility curves are used in a different country (i.e. reinforced concrete buildings in Thailand from the 2004 tsunami and wooden houses in Japan from the 2011 East Japan tsunami). [ABSTRACT FROM AUTHOR]

Emerging as powerful open-source software in recent years, "DualSPHysics" is receiving increased attention for its ability to simulate large-scale flow fields. In the context of applying open-source software, the differences in the numerical results due to different model parameters need to be investigated in detail. In this study, some benchmark problems have been solved with DualSPHysics to validate the estimation of wave impact pressure with violent breaking waves. We have demonstrated three main results: (i) as an alternative to the artificial viscosity traditionally used in DualSPHysics, a laminar viscosity model can also well reproduce the solutions to the existing benchmark problems in a violent flow field with the modified dynamic boundary condition; (ii) the dynamics of the gas phase is essential in the calculation of wave breaking with rapid gate opening; and (iii) if the density diffusion parameter is too large, the impact pressure may be underestimated. The practical contribution by this study is to find that DualSPHysics well reproduces complex breaking waves, including multi-phase gas-liquid flows, and that the wave impact pressure is accurate by comparison with existing experimental results. This allows us to understand the complex behavior of fluid-structure interactions in coastal engineering by means of DualSPHysics. [ABSTRACT FROM AUTHOR]

In the Indian Ocean and the South China Sea, many hundreds of thousands of lives have been lost due to tsunami events, and almost half of the lives lost occurred following the 2004 Indian Ocean event. Potential tsunami case scenarios have been simulated in these regions by a number of researchers to calculate the hazard level. The hazard level is based on a variety of conditions, such as the tsunami height, the inundation area, and the arrival time. However, the current assessments of the hazard levels do not focus on the tsunami risk to a coastal population. This study proposes a new method to quantify the risk to the coastal population in the region that includes the Indian Ocean and the South China Sea. The method is simple and combines the use of readily available tsunami data, far-field tsunami simulation models to determine the regional risk and global population data. An earthquake-generated tsunami was simulated, following an earthquake that had a magnitude larger than 8.5 Mw and occurred along a potential subduction zone. The 2004 Indian Ocean event seemed to be a "worst case scenario"; however, it has been estimated that a potential tsunami, occurring in a coastal region with a high population density, could cause significantly greater casualties. [ABSTRACT FROM AUTHOR]

The study of tsunami hazards in Thailand has been an ongoing topic of research. However, the hazards from tsunami sources based on probabilistic study and population risk are still unclear. In this study, potential tsunami sources along rupture zones were selected. A series of far-field tsunami simulations were performed with scaled fault parameters based on fault lengths from 100-600 km. The results show that within a few centuries, the maximum tsunami height could be 2-5 m at the west coast and less than 2 m at the east coast. The potential tsunami exposure (PTE) of populations in an estimated inundation zone was calculated using global population data in relation to tsunami height. The results show that much attention should be paid to fault ruptures longer than 300 km (≈ 8.5 moment magnitude, Mw) that originate from 4°-6° N and 14°-17° N for the Sumatra subduction zone and the Manila trench, respectively. A quarter of a million people are at risk of exposure to a maximum 9 m tsunami height after 100 min of the arrival of the first wave at the Andaman coast. One million people near the Gulf of Thailand are at risk of a tsunami height less than 3 m after 9 hr. [ABSTRACT FROM AUTHOR]

Japan was hit by the tsunami generated by the greatest earthquake in the history of Japan. The authors conducted the post-tsunami field survey in Miyagi prefecture immediately after the event to measure the inundation depth and investigate damaged buildings. Most of the buildings surveyed were wooden houses and could be classified into 4 damage levels. The primary data of inundation depth and damage levels obtained from the field survey were used to create the tsunami fragility curves, which described the degree of structural damage as a function of the hydrodynamic characteristics of tsunami inundation. The developed fragility curves show that damage with more than a 50% chance of occurring is classified as minor damage, moderate damage, major damage and complete damage when the tsunami inundation depth is between 2.5-3.0 m, 3.0-4.0 m and 4.0-4.5 m and greater than 4.5 m, respectively. By comparing the developed tsunami fragility curves, wooden houses in the studied area have higher structural performance than those obtained from historical events in other areas. The new curves suggest that wooden houses will be severely damaged if the inundation depth is greater than 3 m and collapse if the depth is greater than 4 m while wooden houses from historical data can resist only 1-2 m. Moreover, wooden walls in Japan reduce the overall failure of a structural member because a wooden wall is easier to destroy (compared to brick walls in Thailand and Indonesia) and allows the tsunami to pass through, which reduces the pressure at the attacking front of the tsunami. The fragility curves are very important for the loss estimation and reconstruction plans of the city; they are also crucial for reducing the disaster damage from a future tsunami. [ABSTRACT FROM AUTHOR]

Numerical simulation of tsunami is an effective method to reproduce what has occurred in the past and to predict future events for many tsunami-related research issues including warning systems. However, some real phenomena have not been fully integrated into numerical simulations for transoceanic tsunamis such as fault dynamics of rupture velocity, ocean currents, and the initial sea level. Considering the 2004 Indian Ocean tsunami event, this study evaluates the consequences of rupture velocity. Subsequently, numerical experiments were conducted to normalize the effects as represented by non-dimensional parameters. The rupture velocity, ocean current, and initial sea level were simplified to be uniform and common among simulations. Results of the experiment show that the sea depth along the propagation direction, distance from the tsunami source, rupture velocity, and initial sea level impart some considerable effects on a tsunami's arrival time and wave height. Nevertheless, ocean currents have almost no importance for the arrival time or wave height of oceanic propagation of tsunamis. [ABSTRACT FROM AUTHOR]

Previous applications of machine learning in remote sensing for the identification of damaged buildings in the aftermath of a large-scale disaster have been successful. However, standard methods do not consider the complexity and costs of compiling a training data set after a large-scale disaster. In this article, we study disaster events in which the intensity can be modeled via numerical simulation and/or instrumentation. For such cases, two fully automatic procedures for the detection of severely damaged buildings are introduced. The fundamental assumption is that samples that are located in areas with low disaster intensity mainly represent nondamaged buildings. Furthermore, areas with moderate to strong disaster intensities likely contain damaged and nondamaged buildings. Under this assumption, a procedure that is based on the automatic selection of training samples for learning and calibrating the standard support vector machine classifier is utilized. The second procedure is based on the use of two regularization parameters to define the support vectors. These frameworks avoid the collection of labeled building samples via field surveys and/or visual inspection of optical images, which requires a significant amount of time. The performance of the proposed method is evaluated via application to three real cases: the 2011 Tohoku-Oki earthquake–tsunami, the 2016 Kumamoto earthquake, and the 2018 Okayama floods. The resulted accuracy ranges between 0.85 and 0.89, and thus, it shows that the result can be used for the rapid allocation of affected buildings. [ABSTRACT FROM AUTHOR]

Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In particular, building damage should be assessed to account for possible casualties, and displaced populations, to estimate long-term shelter capacities, and to assess the damage to services that depend on essential infrastructure (e.g. hospitals, schools, etc.). Remote sensing techniques, including satellite imagery, can be used to gathering such information so that the overall damage can be assessed. However, specific points of interest among the damaged buildings need higher resolution images and detailed information to assess the damage situation. These areas can be further assessed through unmanned aerial vehicles and 3D model reconstruction. This paper presents a multi-UAV coverage path planning method for the 3D reconstruction of postdisaster damaged buildings. The methodology has been implemented in NetLogo3D, a multi-agent model environment, and tested in a virtual built environment in Unity3D. The proposed method generates camera location points surrounding targeted damaged buildings. These camera location points are filtered to avoid collision and then sorted using the K-means or the Fuzzy C-means methods. After clustering camera location points and allocating these to each UAV unit, a route optimization process is conducted as a multiple traveling salesman problem. Final corrections are made to paths to avoid obstacles and give a resulting path for each UAV that balances the flight distance and time. The paper presents the details of the model and methodologies, and an examination of the texture resolution obtained from the proposed method and the conventional overhead flight with the nadir-looking method used in 3D mappings. The algorithm outperforms the conventional method in terms of the quality of the generated 3D model. [ABSTRACT FROM AUTHOR]

Rapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time. [ABSTRACT FROM AUTHOR]

Earth observation (EO) technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to continuously monitor ever-growing urban environments. Notably, in the case of large-scale disasters (e.g., tsunamis and earthquakes), in which a response is highly time-critical, images from both data modalities can complement each other to accurately convey the full damage condition in the disaster aftermath. However, due to several factors, such as weather and satellite coverage, which data modality will be the first available for rapid disaster response efforts is often uncertain. Hence, novel methodologies that can utilize all accessible EO datasets are essential for disaster management. In this study, we developed a global multimodal and multitemporal dataset for building damage mapping. We included building damage characteristics from three disaster types, namely, earthquakes, tsunamis, and typhoons, and considered three building damage categories. The global dataset contains high-resolution (HR) optical imagery and high-to-moderate-resolution SAR data acquired before and after each disaster. Using this comprehensive dataset, we analyzed five data modality scenarios for damage mapping: single-mode (optical and SAR datasets), cross-modal (pre-disaster optical and post-disaster SAR datasets), and mode fusion scenarios. We defined a damage mapping framework for semantic segmentation of damaged buildings based on a deep convolutional neural network (CNN) algorithm. We also compared our approach to another state-of-the-art model for damage mapping. The results indicated that our dataset, together with a deep learning network, enabled acceptable predictions for all the data modality scenarios. We also found that the results from cross-modal mapping were comparable to the results obtained from a fusion sensor and optical mode analysis. [ABSTRACT FROM AUTHOR]

To develop disaster mitigation measures in coastal regions affected by earthquakes, it is important to consider the effects of both seismic and tsunami hazards on road structures and assess the social impacts associated with the economic loss and reduction in network functionality. In this paper, a risk- and resilience-based assessment framework is established for road networks under both seismic and tsunami hazards. In the proposed methodology, the risk and resilience are quantified by the economic loss and postdisaster functionality of road networks, respectively. Uncertainties associated with estimations of fault movement, hazard intensity and structural vulnerability are considered when estimating the failure probability using Monte Carlo simulation. Moreover, structural vulnerability against tsunamis is estimated considering the effects of ground motion-induced damage on the reduction in tsunami capacity. As an illustrative example, the road networks in two Japanese cities expected to be affected by the anticipated Nankai Trough earthquake, which would cause strong ground motions and a subsequent tsunami, are analyzed. Finally, the retrofitting prioritization for various structures is discussed based on the risk and resilience quantified as performance indicators for social impacts. [ABSTRACT FROM AUTHOR]

Highly destructive tsunamis occurred near the Pacific coast of Colombia in 1906 and 1979. Recent studies have established asperities within the subduction zone in this area, which can cause megathrust earthquakes triggering highly destructive tsunamis. In this study we assess the tsunami hazard in the main populated areas of Colombia Pacific coast by calculating the inundation depth and the maximum tsunami height from major scenario. A deterministic method is applied using slip deficit models and broadband slip models as tsunami sources. Result suggest that, for the worse-case scenario, the maximum deformation of the seafloor is 6.0 m within the Esmaraldas segment ; the maximum height of the tsunami is 4.66 m, 4.34 m and 0.53 m around. Tumaco Island, Morro Island, and Cascajal Island (Buenaventura Bay), respectively. Two to five meters inundation depth were calculated in over 11% and 10% of the total areas of the islands of Tumaco and Morro, respectively. Based on these result, tsunami hazard maps were alaborated and will serve to create tsunami mitigation plans in these areas. [ABSTRACT FROM AUTHOR]

A fragility function shows the building damage likelihood based on a demand parameter such as the tsunami flow depth. While empirical fragility functions have been developed by using postdisaster damage survey data, regions with no recent tsunami damage cannot develop these estimations. Alternatively, analytical fragility functions could be developed to fill this gap. Along the Colombian Pacific coast, several tsunami events have occurred; however, the aftermath resulting from the structure physical damage was not recorded. Fortunately, other regions of the have collected tsunami damage information, which has been analyzed and represented in terms of empirical fragility functions. This paper provides a comparative study of empirical and analytical tsunami fragility functions. It is focused on the analytical fragility functions developed for typical structures in Tumaco, Colombia and on empirical fragility curves taken from damage survey data of recent tsunami events. The differences in the assessments of the damage produced by the two methods in the case of a two-story reinforced concrete building in Tumaco is discussed herein. As a result of the comparison, it was shown that the structures in Tumaco have higher collapse probabilities at lower flow depths than structures in other places along the Pacific and Indian Oceans. [ABSTRACT FROM AUTHOR]

Applications of machine learning on remote sensing data appear to be endless. Its use in damage identification for early response in the aftermath of a large-scale disaster has a specific issue. The collection of training data right after a disaster is costly, time-consuming, and many times impossible. This study analyzes a possible solution to the referred issue: the collection of training data from past disaster events to calibrate a discriminant function. Then the identification of affected areas in a current disaster can be performed in near real-time. The performance of a supervised machine learning classifier to learn from training data collected from the 2018 heavy rainfall at Okayama Prefecture, Japan, and to identify floods due to the typhoon Hagibis on 12 October 2019 at eastern Japan is reported in this paper. The results show a moderate agreement with flood maps provided by local governments and public institutions, and support the assumption that previous disaster information can be used to identify a current disaster in near-real time. [ABSTRACT FROM AUTHOR]

We developed tsunami fragility functions using three sources of damage data from the 2018 Sulawesi tsunami at Palu Bay in Indonesia obtained from (i) field survey data (FS), (ii) a visual interpretation of optical satellite images (VI), and (iii) a machine learning and remote sensing approach utilized on multisensor and multitemporal satellite images (MLRS). Tsunami fragility functions are cumulative distribution functions that express the probability of a structure reaching or exceeding a particular damage state in response to a specific tsunami intensity measure, in this case obtained from the interpolation of multiple surveyed points of tsunami flow depth. We observed that the FS approach led to a more consistent function than that of the VI and MLRS methods. In particular, an initial damage probability observed at zero inundation depth in the latter two methods revealed the effects of misclassifications on tsunami fragility functions derived from VI data; however, it also highlighted the remarkable advantages of MLRS methods. The reasons and insights used to overcome such limitations are discussed together with the pros and cons of each method. The results show that the tsunami damage observed in the 2018 Sulawesi event in Indonesia, expressed in the fragility function developed herein, is similar in shape to the function developed after the 1993 Hokkaido Nansei-oki tsunami, albeit with a slightly lower damage probability between zero-to-five-meter inundation depths. On the other hand, in comparison with the fragility function developed after the 2004 Indian Ocean tsunami in Banda Aceh, the characteristics of Palu structures exhibit higher fragility in response to tsunamis. The two-meter inundation depth exhibited nearly 20% probability of damage in the case of Banda Aceh, while the probability of damage was close to 70% at the same depth in Palu. [ABSTRACT FROM AUTHOR]

Abstract With the remarkable progress in access to remote sensing imagery data, nowadays research very often utilizes more than one image. We are often able to use multitemporal, hyperspectral, and/or full polarization of microwave radar images. In addition, it has become the general consensus that texture analysis plays an important role in remote sensing. It has been found in several publications that texture analysis was applied to each layer separately; however, this procedure requires a significant amount of computation and produces a massive volume of data. One alternative, and perhaps a better procedure, is to arrange the images into a multi-layered structure and perform texture analysis within some sort of three-dimensional domain. This manuscript extends the concepts of the gray level of co-occurrence matrix (GLCM) texture analysis applied for a single image to a multi-layered set of images, referred to in this paper as 3DGLCM. We then presented an interpretation of the 3DGLCM within the context of building damage identification. A set of 3DGLCM-based features were computed and evaluated as well. As a result, it was observed that some texture features have certain similarities with other methods proposed in previous studies, whereas other features have not been used before. Furthermore, this paper evaluates the performance of the Support Vector Machine (SVM) classifier in learning and detecting collapsed buildings using 3DGLCM-based features. Thus, the empirical evaluation focuses on the identification of collapsed buildings caused by the 2011 Tohoku earthquake and tsunami, where individual polarized TerraSAR-X intensity images are used to compute the texture features, and the collapsed buildings caused by the 2016 Kumamoto earthquake, where LIDAR-based digital surface models are used to compute the texture features. Extensive datasets consisting of building damage states that have been visually inspected by local authorities and research teams are used to set up the training and testing subsets. Furthermore, the proposed texture features are compared with features commonly used to identify collapsed buildings. The study concludes that an SVM trained with 3DGLCM-based features identifies collapsed buildings with high accuracy and outperforms an SVM trained with common features used in previous studies. [ABSTRACT FROM AUTHOR]

The tsunami disasters that occurred in Indonesia, Chile, and Japan have inflicted serious casualties and damaged social infrastructures. Tsunami forecasting systems are thus urgently required worldwide. We have developed a real-time tsunami inundation forecast system that can complete a tsunami inundation and damage forecast for coastal cities at the level of 10-m grid size in less than 20 min. As the tsunami inundation and damage simulation is a vectorizable memory-intensive program, we incorporate NEC’s vector supercomputer SX-ACE. In this paper, we present an overview of our system. In addition, we describe an implementation of the program on SX-ACE and evaluate its performance of SX-ACE in comparison with the cases using an Intel Xeon-based system and the K computer. Then, we clarify that the fulfillment of a real-time tsunami inundation forecast system requires a system with high-performance cores connected to the memory subsystem at a high memory bandwidth such as SX-ACE. [ABSTRACT FROM AUTHOR]

Although supervised machine learning classification techniques have been successfully applied to detect collapsed buildings, there is still a major problem that few publications have addressed. The success of supervised machine learning strongly depends on the availability of training samples. Unfortunately, in the aftermath of a large-scale disaster, training samples become available only after several weeks or even months. However, following a disaster, information on the damage situation is one of the most important necessities for rapid search-and-rescue efforts and relief distribution. In this paper, a modification of the supervised machine learning classification technique called logistic regression is presented. Here, the training samples are replaced with probabilistic information, which is calculated from the spatial distribution of the hazard under consideration and one or more fragility functions. Such damage probabilities can be collected almost in real time for specific disasters such as earthquakes and/or tsunamis. We present the application of the proposed method to the 2011 Great East Japan Earthquake and Tsunami for collapsed building detection. The results show good agreement with a field survey performed by the Ministry of Land, Infrastructure, Transport and Tourism, with an overall accuracy of over 80%. Thus, the proposed method can significantly contribute to a rapid estimation of the number and locations of collapsed buildings. [ABSTRACT FROM AUTHOR]

The 2011 Tohoku Tsunami is considered to be one of the most tragic events in Japan's disaster history, and represents an important milestone for the research community regarding the investigation of the characteristics of tsunami inundation. A thorough analysis of tsunami inundation was conducted using numerical modeling, and measurements from a video recorded from the rooftop of a building in Onagawa in Miyagi Prefecture. In this study, we analyze the destruction of buildings using numerical simulations and tsunami fragility functions. Numerical results for the locations at which the tsunami eyewitness video was recorded are compared with measurements. In addition, we considered the effect of the breakwater in Onagawa bay to evaluate its contribution to reducing overland tsunami inundation depths. The results of our simulations show that the maximum inundation depth due to the first incoming wave was over 16 m, and over 500 buildings were washed away with this first wave. This result is consistent with the video data. Further, we found that the breakwater, which was not originally designed against tsunami waves, reduced the maximum tsunami inundation depth at least by 2.0 m in Onagawa town. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6 m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099 m 3 . Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs. [ABSTRACT FROM AUTHOR]

• A framework for time-variant tsunami hazard assessment considering nonstationary sea-level rise effects is established. • Non-Poisson renewal process models are developed to combine randomly recurring tsunamis with nonstationary sea-level rise. • The sea-level rise uncertainty is integrated during the tsunami hazard assessment according to total probability theorem. • Tsunami hazard increases considerably when considering nonstationary sea-level rise under non-Poisson earthquake events. Tsunami-induced disasters present a significant threat to coastal communities. Under the effects of sea-level rise due to climate change, tsunami occurrence frequency and intensities would increase in a nonstationary manner due to the long-term progressive trend in the variability in sea level. Therefore, the reliability of coastal infrastructure systems affected by tsunami hazard will diminish over time. A procedure for hazard assessment that integrates tsunamis occurring at random times with evolving sea-level rise should be established. This paper presents a novel framework for the time-variant assessment of tsunami hazard considering the effects of nonstationary sea-level rise due to climate change based on a non-Poisson stochastic renewal process. A time-variant probabilistic sea-level rise is modeled by utilizing various climate models and existing data reported in several studies. The conditional tsunami hazard curves considering sea-level rise are estimated by performing tsunami propagation analyses under different sea-level rise cases and by Monte Carlo simulation, considering the uncertainties associated with earthquake fault movements. Finally, the new concept of time-variant tsunami hazard assessment considering the nonstationary effects of sea-level rise is developed according to a non-Poisson stochastic renewal process. An illustrative example is provided by applying the proposed framework to several municipalities in the Kochi Prefecture of Japan that are subjected to the anticipated Nankai-Tonankai earthquake. The effects of sea-level rise on time-variant tsunami hazard under Poisson and non-Poisson processes of earthquake occurrence are discussed. [ABSTRACT FROM AUTHOR]

The 2011 Great East Japan Earthquake generated extreme tsunami waves that entered river mouths, causing strong and long-distance propagation along the water corridors. This study reports the first empirical survey of this rare and extreme ecological impact of tsunami propagation on river communities., We sampled macroinvertebrate communities at 15 river sites on the Sendai Plain in Northeast Japan along a gradient of tsunami disturbance intensity [i.e. altitude: range = 1-29 m above sea level (a.s.l.)] two and 16 months after the earthquake. In comparison with data collected before the tsunami, we found evidence of significant reductions in taxon richness (−54% on average) and total abundance (−91%) after the tsunami in inundated river reaches (up to 25 km from the river mouth)., There were large spatial variations in local impacts, with altitudes of 7-9 m a.s.l. separating heavily damaged inundated communities from intact non-inundated communities., The degraded communities exhibited variable recovery rates extending beyond 16 months after the tsunami. Mobility trait analysis revealed a relatively rapid recovery of swimmers (e.g. Baetis), reflecting their high mobility and active drift behaviours in the recolonisation phase., We observed the rare phenomenon of 'upstream drift' of marine worms (Phyllodocidae) to freshwater rivers in three of the 10 inundated sites. These survived in fresh water for up to 14 months, suggesting that some marine-derived immigrants can persist in fresh water for extended periods. [ABSTRACT FROM AUTHOR]