Kevin D. Henry, & Tim G. Frazier. (2015). Scenario-Based Modeling of Community Evacuation Vulnerability. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Evacuation models can be used to determine evacuation capacity, by estimating the time required for evacuating populations to leave areas exposed to a hazard. Disaster management practices and evacuation modeling are generally carried out to prepare for ?worst-case? conditions. However, hazard severity is highly variable. Performing evacuation modeling for multiple hazard scenarios may provide flexibility and a comprehensive understanding of evacuation capacity. A case study was undertaken to analyze the merit of scenario-based evacuation modeling. Results demonstrate a difference in clearance time between maximum and historic tsunami scenario modeling. During a smaller-scale event, allowing the maximum scenario population to evacuate can add congestion and inhibit evacuation of at-risk populations. Managing evacuation can improve evacuation efficiency by preventing unneeded congestion. Results show that traditional worst-case-scenario modeling may lead to overestimation of time needed to evacuate. Planning under such a scenario may increase risk to smaller-scale hazards.
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Lutiane Queiroz de Almeida, Torsten Welle, & Jörn Birkmann. (2016). A Methodological Proposal to Disaster Risk Indicators in Brazil. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: This article provides a tool to help assess, visualise and communicate different levels of exposure, vulnerability and risk in Brazil. The Disaster Risk Index in Brazil may sensitise public and political decision-makers towards the important topic of disaster risk and climate change adaptation. This article aims to explore the feasibility and usefulness of such a national risk index that considers both natural hazard phenomena and social vulnerability. The results showed that the risk is strongly interwoven with social-economic and cultural conditions and normal everyday life, as well as with the performance of state institutions dealing with Disaster Risk Reduction and Disaster Risk Management, in other words, vulnerability. Spatial trends of disaster risk and vulnerability, products of this research, also have stressed the serious inequalities between and within regions of the country, which result in barriers to the development of the DRR and DRM in Brazil as a whole.
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Miles Crawford, Wendy Saunders, Emma Hudson-Doyle, & David Johnston. (2018). End-user perceptions of natural hazard risk modeling across policy-making, land-use planning, and emergency management within New Zealand local government. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 550–560). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: While the development of risk modelling has focussed on improving model accuracy and modeller expertise, less consideration has been given to understanding how risk models are perceived and used by the end-user. In this think-piece, we explore how risk modelling is perceived and used by three different end-user functions for natural hazard risk management in New Zealand local government: policy-making, land-use planning, and emergency management. We find that risk modelling is: valued and used by policy-makers; less valued within land-use planning and not as widely used; and valued within emergency planning but not as widely used. We offer our thoughts as to why this is the case with reference to focus groups and qualitative interviews held with local government natural hazard risk end-users across the Wellington, Hawke's Bay and Gisborne regions of New Zealand. We conclude with recommendations for how risk modelling can be further developed to increase community resilience.
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