Stochastic Tsunami Research Articles

Probabilistic tsunami hazard assessment for the makran subduction zone using logic tree and stochastic rupture sources

ABSTRACT The Makran Subduction Zone (MSZ) in the northwestern Indian Ocean can generate large tsunamigenic thrust earthquakes affecting the coastal regions of Pakistan, Iran, Oman, and western India. In this paper, a probabilistic tsunami hazard assessment is conducted for the MSZ using stochastic tsunami simulations of moment magnitude (Mw) of 7.7–9.1 earthquake scenarios. This study investigates uncertainties associated with earthquake occurrence rate, single-segment (eastern and western MSZ) or two-segment (full MSZ) rupture scenarios, source geometry, and slip heterogeneity. The total number of simulated source models is 15,000. This study presents two major categories of results: stochastic source models and ranges of 475, 975, and 2475-year tsunami heights. For instance, tsunami heights generated by Mw 8.5‒8.7 stochastic sources of western MSZ vary between 1 m and 10 m with a mean of ~ 4.5 m in the affected areas. The tsunami heights are sensitive to the source models’ characteristics, such as location of the large slip areas, bathymetry of the nearshore area, and the location of bays. Considering different occurrence rates results in significant variability in the estimated 475, 975, and 2475-year tsunami heights. For example, 2475-year tsunami height in Chabahar is in the range of 3‒7.4 m at 10 m water depth.

Integrated tsunami risk framework considering agent-based evacuation modelling: The case of Saga, Kochi Prefecture, Japan

This study develops an integrated tsunami risk framework combining stochastic tsunami hazard and agent-based evacuation modelling. The framework is applied to the case of Saga, Kochi, Japan, with a population of ∼ 2,200 anticipated to experience significant tsunami events (∼ M9.0). First, stochastic earthquake source models are generated for two values of magnitudes (M8.8 and M9.0) and used to carry out stochastic tsunami inundation simulations. Agent-based tsunami evacuation modelling using MATSim is then performed by considering four mode scenarios: single mode (pedestrian and car) and two multimodal scenarios (mix of car and pedestrian). The stochastic tsunami simulations and agent-based evacuation modelling results are integrated to estimate the risk. The effect of existing tsunami evacuation points and tsunami evacuation towers on risk reduction is also assessed. Such an integration framework is finally used to recommend tsunami mitigation strategies in the tsunami-prone regions. Results show that a significant tsunami hazard (i.e., tsunami depth up to 15 m) is expected in the Saga district, with an arrival time between 5 and 30 min. In addition, the evacuation points on higher grounds effectively save local residents' lives, as shown by the small number of affected people, specifically for the pedestrian and multimodal models (i.e. 10-100 people, excluding the car model). However, up to ∼ 1,000 people may get affected if car is the sole mode of evacuation. Therefore, the coastal community is recommended to evacuate on foot. Finally, identifying and securing sufficient higher grounds and vertical evacuation points are essential for risk reduction.

Improvement to stochastic tsunami hazard analysis of megathrust earthquakes for western Makran subduction zone

The Makran Subduction Zone (MSZ) is one of the world's most tsunami-prone regions. In the present study, tsunami hazards associated with potential MSZ earthquakes are evaluated using stochastic earthquake rupture modeling, which allows for the incorporation of uncertainties related to slip heterogeneity. Along the western segment of the MSZ, where tsunami hazard studies have received less attention, megathrust earthquakes with moment magnitudes of Mw 8.5, 8.7, and 8.9 are considered. The source parameters of 600 stochastic earthquake scenarios are calculated using the scaling relationships of Goda et al. (2016), which represent significant improvements over previous scaling relationships by taking into account the uncertainty of multiple source parameters and the coverage of a wide range of earthquake magnitudes. In order to simulate tsunami propagation and inundation, the nonlinear shallow water equations are used in four-level nested grid model domains .According to the calculated slip fields, the seismic source characteristics provided by stochastic source models significantly change within the earthquakes scenarios with identical magnitudes and may completely differ from the results of traditional uniform-slip source models. The results of the 600 Monte Carlo tsunami simulations demonstrate that even extremely large earthquakes in the west MSZ do not lead to significant tsunamis along the eastern coastal regions of Makran. The average maximum wave heights of 8, 10, and 17 m along the western Makran coasts, which correspond to the Mw 8.5, 8.7, and 8.9 scenarios, respectively, emphasize the severe potential threat of a possible tsunamigenic event in the west of the MSZ to the Iranian coasts. In addition, the significant difference between the maximum wave heights of the 10th and 90th percentiles for each scenario demonstrates the large variability of tsunami heights resulting from uncertainties associated with stochastic seismic source modeling. Thus, it can be concluded that the tsunami hazard parameters estimated by simple uniform-slip source models need to be revised in future tsunami risk assessment studies.

Stochastic tsunami modeling induced by kinematic complex sources

In this study, local tsunami hazard due to seismic sources is evaluated in a stochastic framework. Several assumptions such as static passive generation, constant rake angle and source centroid (among others) are relaxed. Spatial uncertainties are modeled in a large set of scenarios. The proposed methodology is easy to implement and can be combined with other types of sources or hazards. Application in the Kuril-Kamchatkah trench shows a straightforward use of our methodology, producing simple hazard maps, which can be replicated in any region of the world.

Stochastic source modeling and tsunami simulations of cascadia subduction earthquakes for Canadian Pacific coast

ABSTRACT This study presents new stochastic source models for the Cascadia subduction earthquakes in the Pacific Northwest, which can trigger massive tsunamis along the shoreline of Vancouver Island. An extensive set of 5,000 stochastic source models is generated for the moment magnitude ranges between 8.1 and 9.1, and regional tsunami hazard simulations are performed at the grid resolution of 270 m. The results from the stochastic tsunami simulations are characterized by evaluating the regional tsunami hazard metric that is based on the geometric mean of the maximum wave heights along the Vancouver Island coast. Subsequently, using the probability distribution of the regional tsunami hazard parameter, representative source models are identified by capturing the average as well as rare rupture cases and then detailed tsunami hazard results, such as maximum wave height maps and wave profiles at specific locations, are examined. Numerical results highlight the directivity effects of tsunami generation and wave propagation on tsunami hazards along the Canadian Pacific coast and the earthquake source characterizations in terms of fault geometry and earthquake slip distribution. The developed source models and tsunami simulation results serve as the first step for performing probabilistic tsunami hazard analysis for the Cascadia subduction zone.

Hazard and Risk-Based Tsunami Early Warning Algorithms for Ocean Bottom Sensor S-Net System in Tohoku, Japan, Using Sequential Multiple Linear Regression

This study presents robust algorithms for tsunami early warning using synthetic tsunami wave data at ocean bottom sensor (OBS) arrays with sequential multiple linear regression. The study focuses on the Tohoku region of Japan, where an S-net OBS system (150 pressure sensors) has been deployed. To calibrate the tsunami early warning system using realistic tsunami wave profiles at the S-net stations, 4000 stochastic tsunami simulations are employed. Forecasting models are built using multiple linear regression together with sequential feature selection based on Akaike Information Criterion and knee-point method to identify sensors that improve the accuracy most significantly. The study considers tsunami wave amplitude at a nearshore location and regional tsunami loss for buildings to develop hazard-based and risk-based tsunami warning algorithms. The models identify an optimal configuration of OBS stations and waiting time for issuing tsunami warnings. The model performance is compared against a base model, which only uses the earthquake magnitude and epicenter location. The result indicates that estimating the tsunami amplitude and loss via S-net improves accuracy. For the hazard-based forecasting, adding six sensors from the S-net improves the accuracy of the estimation most significantly with an optimal waiting time of 3 min. For the risk-based forecasting, a longer waiting time between 5 and 10 min is suitable.

Distinctive Stochastic Tsunami Hazard and Environmental Risk Assessment of Akkuyu Nuclear Power Plant by Monte Carlo Simulations

Distinctive Stochastic Tsunami Hazard and Environmental Risk Assessment of Akkuyu Nuclear Power Plant by Monte Carlo Simulations

Are current tsunami evacuation approaches safe enough?

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.

Stochastic Analysis of Tsunami Hazard of the 1945 Makran Subduction Zone Mw 8.1–8.3 Earthquakes

Historical records of major earthquakes in the northwestern Indian Ocean along the Makran Subduction Zone (MSZ) indicate high potential tsunami hazards for coastal regions of Pakistan, Iran, Oman, and western India. There are fast-growing and populous cities and ports that are economically important, such as Chabahar (Iran), Gwadar (Pakistan), Muscat (Oman), and Mumbai (India). In this study, we assess the tsunami hazard of the 1945 MSZ event (fatalities ≈300 people) using stochastic earthquake rupture models of Mw 8.1–8.3 by considering uncertainties related to rupture geometry and slip heterogeneity. To quantify the uncertainty of earthquake source characteristics in tsunami hazard analysis, 1000 stochastic tsunami scenarios are generated via a stochastic source modeling approach. There are main objectives of this study: (1) developing stochastic earthquake slip models for the MSZ, (2) comparing results of the simulation with the existing observations of the 1945 event, and (3) evaluating the effect of uncertain fault geometry and earthquake slip based on simulated near-shore wave profiles. The 1945 Makran earthquake is focused upon by comparing model predictions with existing observations, consisting of far-field tsunami waveforms recorded on tide gauges in Karachi and Mumbai and coseismic deformation along the Pakistani coast. The results identify the source model that matches the existing observations of the 1945 Makran event best among the stochastic sources. The length, width, mean slip, and maximum slip of the identified source model are 270 km, 130 km, 2.9 m, and 19.3 m, respectively. Moreover, the sensitivity of the maximum tsunami heights along the coastline to the location of a large-slip area is highlighted. The maximum heights of the tsunami and coseismic deformation results at Ormara are in the range of 0.3–7.0 m and −2.7 to 1.1 m, respectively, for the 1000 stochastic source models.

Uncertainty quantification of tsunami inundation in Kuroshio, Kochi Prefecture, Japan, using the Nankai–Tonankai megathrust rupture scenarios

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.

An improvement of tsunami hazard analysis in Central Chile based on stochastic rupture scenarios

ABSTRACT 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 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.

Influence of Elevation Data Resolution on Tsunami Loss Estimation and Insurance Rate-Making

Tsunamis triggered by large offshore earthquakes are devastating, and buildings located near the coast experience damage and loss due to such extreme events. In evaluating regional tsunami impact via numerical tsunami simulations, it is important to pay close attention to local geographical features represented by a digital elevation model (DEM), because tsunami loss estimation is sensitive to its quality and resolution. This study investigates the influence of elevation data resolution on tsunami loss estimation at different scales by comparing tsunami risk results using DEMs of four resolutions (i.e. 10-m, 50-m, 150-m, and 450-m). Using stochastic tsunami modelling, a case study is carried out by focusing on the Tohoku region in Japan to investigate the influence of DEM resolution on tsunami loss estimation considering the effect of location attributes (i.e. coastal topography, distance from the coast, and land elevation) for two building portfolios on plain coast and ria coast. The results indicate the significance of DEM resolution for local tsunami loss estimations at different locations. The local tsunami risk is closely related to the building location, and the increase of distance from the coast and/or land elevation dramatically reduces the local tsunami risk. The investigations extend discussions regarding the calculations of pure insurance premium rate for tsunami loss coverage depending upon structural attributes and location attributes.

Rapid tsunami loss estimation using regional inundation hazard metrics derived from stochastic tsunami simulation

This study explores the development of rapid tsunami loss estimation approaches that are based on regional inundation hazard metrics, such as representative inundation height and inundation area. In post-tsunami situations, these inundation hazard metrics can be inferred from remotely-sensed images. Using a probabilistic tsunami loss model for the Tohoku region of Japan, rapid tsunami loss estimation models are developed by regressing predicted tsunami losses against regional inundation hazard parameters, which are derived for coastal cities and towns in Miyagi Prefecture from 4000 stochastic tsunami simulations. Using numerous earthquake sources of moment magnitudes between 7.5 and 9.1 facilitates the robust development of a quick tsunami loss estimation tool. Special considerations are given in investigating the effects of coastal topography (plain versus ria) and the potential bias due to errors in estimating inundation heights and areas on tsunami loss. Performances of the new approaches are compared with conventional methods that are based on earthquake magnitude, source-to-site distance, and offshore tsunami wave profiles. The loss models based on regional inundation area outperform other approaches and thus are recommended for regional tsunami loss estimation.

Tsunami evacuation plans for future megathrust earthquakes in Padang, Indonesia, considering stochastic earthquake scenarios

Abstract. This study develops tsunami evacuation plans in Padang, Indonesia, using a stochastic tsunami simulation method. The stochastic results are based on multiple earthquake scenarios for different magnitudes (Mw 8.5, 8.75, and 9.0) that reflect asperity characteristics of the 1797 historical event in the same region. The generation of the earthquake scenarios involves probabilistic models of earthquake source parameters and stochastic synthesis of earthquake slip distributions. In total, 300 source models are generated to produce comprehensive tsunami evacuation plans in Padang. The tsunami hazard assessment results show that Padang may face significant tsunamis causing the maximum tsunami inundation height and depth of 15 and 10 m, respectively. A comprehensive tsunami evacuation plan – including horizontal evacuation area maps, assessment of temporary shelters considering the impact due to ground shaking and tsunami, and integrated horizontal–vertical evacuation time maps – has been developed based on the stochastic tsunami simulation results. The developed evacuation plans highlight that comprehensive mitigation policies can be produced from the stochastic tsunami simulation for future tsunamigenic events.

Influence of Flow Velocity on Tsunami Loss Estimation

Inundation depth is commonly used as an intensity measure in tsunami fragility analysis. However, inundation depth cannot be taken as the sole representation of tsunami impact on structures, especially when structural damage is caused by hydrodynamic and debris impact forces that are mainly determined by flow velocity. To reflect the influence of flow velocity in addition to inundation depth in tsunami risk assessment, a tsunami loss estimation method that adopts both inundation depth and flow velocity (i.e., bivariate intensity measures) in evaluating tsunami damage is developed. To consider a wide range of possible tsunami inundation scenarios, Monte Carlo-based tsunami simulations are performed using stochastic earthquake slip distributions derived from a spectral synthesis method and probabilistic scaling relationships of earthquake source parameters. By focusing on Sendai (plain coast) and Onagawa (ria coast) in the Miyagi Prefecture of Japan in a case study, the stochastic tsunami loss is evaluated by total economic loss and its spatial distribution at different scales. The results indicate that tsunami loss prediction is highly sensitive to modelling resolution and inclusion of flow velocity for buildings located less than 1 km from the sea for Sendai and Onagawa of Miyagi Prefecture.

Probabilistic Tsunami Hazard Analysis of the Pacific Coast of Mexico: Case Study Based on the 1995 Colima Earthquake Tsunami

This study develops a novel computational framework to carry out probabilistic tsunami hazard assessment for the Pacific coast of Mexico. The new approach enables the consideration of stochastic tsunami source scenarios having variable fault geometry and heterogeneous slip that are constrained by an extensive database of rupture models for historical earthquakes around the world. The assessment focuses upon the 1995 Jalisco-Colima Earthquake Tsunami from a retrospective viewpoint. Numerous source scenarios of large subduction earthquakes are generated to assess the sensitivity and variability of tsunami inundation characteristics of the target region. Analyses of nine slip models along the Mexican Pacific coast are performed and statistical characteristics of slips (e.g. coherent structures of slip spectra) are estimated. The source variability allows exploring a wide range of tsunami scenarios for a moment magnitude (Mw) 8 subduction earthquake in the Mexican Pacific region to conduct thorough sensitivity analyses and to quantify the tsunami height variability. The numerical results indicate a strong sensitivity of maximum tsunami height to major slip locations in the source, and indicate major uncertainty at the first peak of tsunami waves.

Tsunami Hazard Analysis of Future Megathrust Sumatra Earthquakes in Padang, Indonesia Using Stochastic Tsunami Simulation

This study assesses the tsunami hazard potential in Padang, Indonesia probabilistically using a novel stochastic tsunami simulation method. The stochastic tsunami simulation is conducted by generating multiple earthquake source models for a given earthquake scenario, which are used as input to run Monte Carlo tsunami simulation. Multiple earthquake source models for three magnitude scenarios, i.e. Mw 8.5, Mw 8.75, and Mw 9.0, are generated using new scaling relationships of earthquake source parameters developed from an extensive set of 226 finite-fault models. In the stochastic tsunami simulation, the effect of incorporating and neglecting the prediction errors of earthquake source parameters is investigated. In total, 600 source models are generated to assess the uncertainty of tsunami wave characteristics and maximum tsunami wave height profiles along coastal line of Padang. The results highlight the influence of the uncertainty of the scaling relationships on tsunami simulation results and provide a greater range of tsunamigenic scenarios produced from the stochastic tsunami simulation. Additionally, the results show that for the future major earthquakes in the Sunda megathrust, the maximum tsunami wave height in Padang areas can reach 20 m and therefore, significant damage and loss may be anticipated in this region.

New Scaling Relationships of Earthquake Source Parameters for Stochastic Tsunami Simulation

New scaling relationships of key earthquake source parameters are developed by uniformly and systematically analyzing 226 finite-fault rupture models from the SRCMOD database (http://equake-rc.info/srcmod/). The source parameters include the fault width, fault length, fault area, mean slip, maximum slip, Box-Cox power, correlation lengths along dip and strike directions, and Hurst number. The scaling relationships are developed by distinguishing tsunamigenic models from non-tsunamigenic models; typically, the former occurs in ocean and has gentler dip angles than the latter. The new models are based on extensive data, including recent mega-thrust events, and thus Eire more reliable. Moreover, they can be implemented as multivariate probabilistic models that take into account uncertainty and dependency of the multiple source parameters. The comparison between new and existing models indicates that the new relationships are similar to the existing ones for earthquakes with magnitudes up to about 8.0, whereas the relationships for the fault width and related parameters differ significantly for larger mega-thrust events. An application of the developed scaling relationships in tsunami hazard analysis is demonstrated by synthesizing stochastic earthquake source models in the Tohoku region of Japan. The examples are aimed at providing practical guidance as to how the developed scaling relationships can be implemented in stochastic tsunami simulation. The numerical results indicate that the effects of magnitude scaling of the source parameters and their uncertainties have major influence on the tsunami hazard assessment.

Probabilistic Tsunami Damage Assessment Considering Stochastic Source Models: Application to the 2011 Tohoku Earthquake

A computational framework for probabilistic tsunami risk assessment due to a mega-thrust subduction earthquake is developed and is applied to the 2011 Tohoku Tsunami from retrospective viewpoints. The uncertain tsunami source characteristics are represented by multiple source inversion models and their stochastic variations that are generated using the spectral analysis and synthesis method. By conducting Monte Carlo tsunami simulation, stochastic inundation depth maps can be developed, which are subsequently integrated with tsunami fragility curves to develop stochastic tsunami risk maps. The stochastic tsunami risk maps display spatial variability of tsunami damage probabilities for a building portfolio, reflecting not only possible tsunami scenarios but also uncertain tsunami resistance of buildings. The numerical results indicate that both stochastic tsunami risk maps and risk curves are affected by the local terrain features, proximity to major tsunami sources, and building characteristics (material type and story number). Consideration of different reference tsunami source models in probabilistic tsunami risk assessment are identified as one of the critical contributors to the overall uncertainty of the tsunami risk predictions. Therefore, in determining critical scenarios for tsunami evacuation and risk mitigation, a wide range of possible tsunami scenarios should be considered in light of the current limited seismological knowledge for the mega-thrust subduction earthquake.

Uncertainty modeling and visualization for tsunami hazard and risk mapping: a case study for the 2011 Tohoku earthquake

This study presents a rigorous computational framework for visualizing uncertainty of tsunami hazard and risk assessment. The methodology consists of three modules: (i) earthquake source characterization and stochastic simulation of slip distribution, (ii) tsunami propagation and inundation, and (iii) tsunami damage assessment and loss estimation. It takes into account numerous stochastic tsunami scenarios to evaluate the uncertainty propagation of earthquake source characteristics in probabilistic tsunami risk analysis. An extensive Monte Carlo tsunami inundation simulation is implemented for the 2011 Tohoku tsunami (focusing upon on Rikuzentakata along the Tohoku coast of Japan) using 726 stochastic slip models derived from eleven inverted source models. By integrating the tsunami hazard results with empirical tsunami fragility functions, probabilistic tsunami risk analysis and loss estimation are carried out; outputs from the analyses are displayed using various visualization methods. The developed framework is comprehensive, and can provide valuable insights in promoting proactive tsunami risk management and in improving emergency response capability.