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.

An important, but overlooked component of disaster managment is raising the awareness and preparedness of potential stakeholders. We show how recent advances in agent-based modeling and geo-information analytics can be combined to this effect. Using a dynamic simulation model, we estimate the long run outcomes of two very different urban disasters with severe consequences: an earthquake and a missile attack. These differ in terms of duration, intensity, permanence, and focal points. These hypothetical shocks are simulated for the downtown area of Jerusalem. Outcomes are compared in terms of their potential for disaster mitigation. The spatial and temporal dynamics of the simulation yield rich outputs. Web-based mapping is used to visualize these results and communicate risk to policy makers, planners, and the informed public. The components and design of this application are described. Implications for participatory disaster management and planning are discussed.

An agent based (AB) simulation model of urban dynamics following a disaster is presented. Data disaggregation is used to generate ‘synthetic’ data with accurate socio-economic profiling. Entire synthetic populations are extrapolated at the building scale from survey data. This data is coupled with the AB model. The disaggregated baseline population allows for the bottom-up formulation of the behavior of an entire urban system. Agent interactions with each other and with the environment lead to change in residence and workplace, land use and house prices. The case of a hypothetical earthquake in the Jerusalem CBD is presented as an illustrative example. Dynamics are simulated for a period up to 3 years, post-disaster. Outcomes are measured in terms of global resilience measures, effects on residential and non-residential capital stock and population dynamics. The visualization of the complex outputs is illustrated using dynamic web-mapping.

In plain areas prone to tsunami, finding a way to shelter and escape from the inundation becomes a difficult task for residents. The 2011 Great East Japan Tsunami has shown that the horizontal evacuation using cars can compromise the safety of people. Another alternative is the vertical evacuation. In many cases, not only the capacity of these shelters plays an important role, but the spatial distribution and the evacuee preference for the nearest shelter. Such preference and location creates a conflict between capacity offer and demand. In this paper, we used an agent based model to simulate the evacuation of pedestrians and cars in La Punta, Peru. Twenty designated buildings for vertical evacuation are available for sheltering and escape from tsunami. The stochastic simulation of population spatial distribution and their refuge preferences revealed the over demand of some shelters. Finally, a capacity-demand map was created to share results with local authorities as a first step for future countermeasures in the district.

While the direct physical effects of an urban catastrophe are relatively straightforward to assess, indirect and long-term impact on the urban system is more circumspect. A large-scale shock such as an earthquake derails the complex urban system from its equilibrium path onto an unknown trajectory. Consequently, assessing the effect of policy intervention that aims to mitigate this shock and increase urban resilience is fraught with complexity. This paper presents the implementation of dynamic agent-based simulation to test long-run effects of a hypothetical earthquake in Jerusalem, Israel. It focuses on investigating the effectiveness of policy choices aimed at restoring the urban equilibrium. Cities are found to have a self-organising market-based mechanism that strives to attain a new equilibrium. They therefore may not always bounce back – they may also bounce forward. Decision-makers, engineers, emergency and urban planners need to be cognizant of this tendency when designing policy interventions. Otherwise, well-intentioned efforts may inhibit urban rejuvenation and delay the onset of city recovery.

This paper assesses the socioeconomic consequences of extreme coastal flooding events. Wealth and income impacts associated with different social groups in coastal communities in Israel are estimated. A range of coastal flood hazard zones based on different scenarios are identified. These are superimposed on a composite social vulnerability index to highlight the spatial variation in the socioeconomic structure of those areas exposed to flooding. Economic vulnerability is captured by the exposure of wealth and income. For the former, we correlate the distribution of housing stock at risk with the socioeconomic characteristics of threatened populations. We also estimate the value of residential assets exposed under the different scenarios. For the latter, we calculate the observed change in income distribution of the population under threat of inundation. We interpret the change in income distribution as an indicator of recovery potential.

Humanitarian logistics has gain attention as an important tool in disaster management. We propose a network design for relief distribution under several uncertain parameters based on robust optimization. The model has the solution robustness and model robustness properties. Furthermore, we present a methodology to reduce the number of variables when an equality constraint and objective function contain same variables. Our model attempts to minimize total cost of the system as well as the variance of total cost. We examine a case study on the earthquake scenarios in Bangladesh to show the applicability of the model. Our findings show that the model is robust in relief distribution planning. We analyze sensitivity of several parameters and compare several models to show the superiority of stochastic model.

A large amount of buildings was damaged or destroyed by the 2011 Great East Japan tsunami. Numerous field surveys were conducted in order to collect the tsunami inundation extents and building damage data in the affected areas. Therefore, this event provides us with one of the most complete data set among tsunami events in history. In this study, fragility functions are derived using data provided by the Ministry of Land, Infrastructure and Transportation of Japan, with more than 250,000 structures surveyed. The set of data has details on damage level, structural material, number of stories per building and location (town). This information is crucial to the understanding of the causes of building damage, as differences in structural characteristics and building location can be taken into account in the damage probability analysis. Using least squares regression, different sets of fragility curves are derived to demonstrate the influence of structural material, number of stories and coastal topography on building damage levels. The results show a better resistant performance of reinforced concrete and steel buildings over wood or masonry buildings. Also, buildings taller than two stories were confirmed to be much stronger than the buildings of one or two stories. The damage characteristic due to the coastal topography based on limited number of data in town locations is also shortly discussed here. At the same tsunami inundation depth, buildings along the Sanriku ria coast were much greater damaged than buildings from the plain coast in Sendai. The difference in damage states can be explained by the faster flow velocities in the ria coast at the same inundation depth. These findings are key to support better future building damage assessments, land use management and disaster planning.

The 2011 Great East Japan earthquake and tsunami was a magnitude 9.0 Mw event that destroyed most structural tsunami countermeasures. However, approximately 90% of the estimated population at risk from the tsunami survived due to a rapid evacuation to higher ground or inland. Thus, tsunami evacuation is the most effective measure to reduce casualties. In this paper, we applied a new developed evacuation model integrated with the numerical simulation of tsunami for casualty estimation. This tool is to support decisions in disaster management and disaster prevention education. The model was developed in NetLogo, a multi-agent programming language and modeling environment for simulating complex phenomena. Geographic Information Systems (GIS) datasets are used as spatial input information for road and shelter locations. The TUNAMI model of Tohoku University is used for the integration of tsunami numerical simulation results. In this paper, the study is performed in a tsunami threatened urban area of Callao, Peru, called La Punta. Results show the various contributions of the model to disaster management and scenario analysis. Among the contributions are the casualty estimation in a tsunami risk area and the analysis of the spatial distribution of vertical evacuation shelters.

The 2011 Great East Japan Earthquake/Tsunami was a magnitude 9.0 Mw event that destroyed most structural tsunami countermeasures. However, approximately 90% of the estimated population at risk from the tsunami survived due to rapid evacuation to higher ground or inland. In this paper, we introduce an evacuation model integrated with a numerical simulation of a tsunami and a casualty estimation evaluation. The model was developed in Netlogo, a multi-agent programming language and modeling environment for simulating complex phenomena. GIS data are used as spatial input information for road and shelter locations. Tsunami departure curves are used as the start time for agents deciding to evacuate in the model. Pedestrians and car drivers decide their own goals and search for a suitable route through algorithms that are also used in the video game and artificial intelligence fields. Bottleneck identification, shelter demand, and casualty estimation are some of the applications of the simulator. A case study of the model is presented for the village of Arahama in the Sendai plain area of Miyagi Prefecture in Japan. A stochastic simulation with 1,000 repetitions of evacuation resulted in a mean of 82.1% (SD=3.0%) of the population evacuated, including a total average of 498 agents evacuating to a multi-story shelter. The results agree with the reported outcome of 90% evacuation and 520 sheltered evacuees in the event. The proposed model shows the capability of exploring individual parameters and outcomes. The model allows observation of the behavior of individuals in the complex process of tsunami evacuation. This tool is important for the future evaluation of evacuation feasibility and shelter demand analysis.

This paper presents a systematic framework for assessing the costs of sea-level rise (SLR) and extreme flooding at the local level. The method is generic and transferable. It is built on coupling readily available GIS capabilities with quantitative estimates of the effects of natural hazards. This allows for the ex ante monetization of the main costs related to different scenarios of permanent inundation and periodic flooding. This approach can be used by coastal zone planners to generate vital information on land use, capital stock and population at risk for jurisdictions of different sizes. The simple mechanics of the method are presented with respect to two examples: one relates to the two largest coastal cities in Israel (Tel Aviv and Haifa) and the other to the Northern Coastal Strip region containing a variety of small towns and rural communities. The paper concludes with implications for coastal zone planning praxis.