How can the human dimensions of disaster impacts be more accurately captured and represented in the analysis, modeling and simulation of disasters?
Natural hazards can adversely impact the built and socioeconomic environments in terms of direct losses; such as initial damage to physical infrastructure; functionality; and recovery; and indirect losses; such as the casualty; employment; household income; and local tax revenue. Here are the main points for future research that involve human dimensions. First; decision-makers and emergency planners are inclined to estimate the impact of the “high-risk” rather than “worst-case” scenarios at the community level; which requires estimating both the probability of occurrence of the hazards and their consequences; such as those involving human dimensions. Second; a consistent definition of building functionality must be established due to its importance for evaluating both direct and indirect losses. Third; while most studies to date have mainly used census data to derive population characteristics; considering a high-resolution spatial (parcel level) and temporal population layer (daytime vs. nighttime) improves the accuracy of results; particularly for communities with high levels of tourism. Fourth; the interaction between direct and indirect losses needs to be included in the modeling to achieve more realistic and accurate results (e.g.; the effect of casualty and outmigration on short-run economic losses). Lastly; more studies are required to validate both direct and indirect losses at parcel and community levels based on existing data as well as data collected from pre- and post-disaster communities in the future.
What type of data and supporting research infrastructure would be necessary to enable novel, transdisciplinary approaches to answering these and other human-centered disaster questions?
Various types of pre- and post-disaster data must be collected to develop models; validate results; and finally answer human-centered disaster problems. First; the built environment; consisting of different infrastructure systems; including buildings; transportation network; electric power network; and water supply network needs to be well-defined in order to have a high-resolution engineering-economic model. There are several databases that can be utilized to collect data; including tax lot data; Google Street view; field survey; aerial imagery; and other public/private datasets; including population layers and demographic characteristics. However; data standards and metrics; and data sharing requirements; may be different in US and Japan; which may inform what is available for modeling in various communities. Second; following a natural disaster; additional reconnaissance data needs to be collected to develop and later validate fragility and functionality functions. For example; post-disaster data collection can be utilized to validate the definition of building functionality in the vulnerability analysis. Third; post-disaster data is also essential at the community level to validate simulation results derived from different economic models; such as the computable general equilibrium (CGE) model; if useful in Japan. For example; short- and long-term employment and real household income losses and corresponding recovery times derived from simulations should be validated at the community level. Lastly; conducting surveys is another way to collect data that can be used in different simulations. For example; several surveys have been conducted in coastal communities vulnerable to tsunami hazards in order to estimate the preparation time of people during the tsunami evacuation.
In what ways can US-Japan collaborations advance these questions in new and important ways?
Natural hazards can threaten people and cause direct and indirect economic losses in both developing and developed countries. The US and Japan; as developed countries; are vulnerable to a wide range of natural disasters resulting in significant human and economic losses. Hurricane Katrina in 2005 and Kobe Earthquake in 1995 are such examples of devastating natural disasters in the US and Japan resulting in $75 billion and $100 billion in damage; respectively. Similarly; early studies about the tsunami evacuation have been carried out in Japan due to its extensive experience with tsunamis such as the 2011 East Japan tsunamis. As a result; both the US and Japan have developed emergency management systems and developed lessons learned to aid in disaster preparedness. There are several ways that the US and Japan can collaborate to advance these questions. First; sharing reconnaissance data; including both pre- and post-disaster data and surveys that can benefit researchers interested in human-centered disaster problems. Although the political system; emergency management system; and cultural system in the US and Japan have major differences; exchanging data; ideas; and experiences are effective ways toward answering these questions. Second; holding workshops with researchers from both US and Japanese universities helps researchers to exchange ideas; experiences; and unique problems. These workshops can have various objectives such as (1) comparing building codes and design standards; (2) numerical model benchmarking (e.g.; life safety and economic modeling); (3) roles and players in situational decision making during and following disasters; (4) availability and security legislation surrounding data use.