Anticipating Interpretations and Reactions to Earthquake Early Warnings
Ann BOSTROM (USA)
Emergency Management Decision-Making in the Laboratory: the Case of Uncertain Volcanic Advice
Emma HUDSON-DOYLE (New Zealand)
Promoting “Behavioural Disaster Management” toward Disaster Risk Reduction by Design
Haruo HAYASHI (Japan)
A New Focus on Risk Reduction: an Ad-Hoc Decision Support System for Humanitarian Relief Logistics
Frank SCHÄTTER (Germany)
Weyerhaeuser Professor of Environmental Policy, Daniel J. Evans School of Public Affairs, University of Washington, Seattle, USA
Early earthquake warning (EEW) systems hold great promise. The few EEW systems deployed around the world have helped prevent and mitigate damages from earthquakes. While the technologies to detect threats, their reliability, and the length of time needed to achieve accuracy in forecasts and predictions in EEW are important factors in achieving this, equally important are how EEW rely on human mediation; channels for issuing warnings; familiarity and institutionalisation of warning procedures; settings in which systems are used; and system goals and objectives. In other words, how early earthquake alerts and warnings are interpreted and what actions people take in response to them depend on cognitive, emotive, social and institutional contexts, as well as on their natural and built environment. A key lesson from prior research on hazard warnings is that people need actionable information on what to do, not just that there is a threat. With seconds to minutes of lead time, accomplishing this will require setting the stage for action by working with communities and institutions to develop goals, procedures, and expectations. This talk characterises the initial phases of EEW development in the Pacific Northwest of the USA, based on prior risk interpretation and action research and initial interviews with Pacific Northwest Seismic Network leaders and affiliates. This research is funded by U.S. NSF EAR-1331412 grant.
Emma HUDSON-DOYLE1, Douglas PATON2 and David M. JOHNSTON1
- Joint Centre for Disaster Research, Massey University, Wellington, NZ
- School of Psychology, University of Tasmania, Tasmania, Australia
Successful emergency management decision-making during natural hazard events is fundamentally dependent upon individual and team situation awareness (i.e. how selection, interpretation, and understanding of available information define the problem and identify solutions) while operating under high time and risk pressures. The development and evolution of situational awareness, and thus response effectiveness, is critically dependent upon the information and advice from external experts. However, this advice is characterised by both stochastic uncertainty (the variability of the system) and epistemic uncertainty (lack of knowledge). This can constrain decision-making and block or delay action. While behavioural decision theories have identified heuristics for coping with such uncertainty, less is known about how these operate in emergency settings to help decision-makers understand, acknowledge, and manage uncertainties in information sources and in complex physical systems. Exploring this is the topic of this paper.
We explored how provision of science advice influenced emergency decisions during natural hazard events using real time group exercises (three full day exercises with four to six practitioners) to investigate how personnel create Situation Reports and Incident Action Plans based on a range of injects for a volcanic eruption, with a particular focus on uncertain science advice and the communication of non-consensus advice. During this exercise, the participants received injects representing scientific information and agency communications (from police, media, the public, etc.). Data were obtained from recordings of group activity, questionnaires and debriefs about the processes they went through, the key issues identified, what information they were looking for during the hypothetical event, and what they would do differently.
We discuss the development and conduct of these exercises and present findings covering how participants self-organised in exercise settings, how they reacted to, utilised and understood scientific information, how they coped with the prevailing scientific uncertainty and corresponding disagreement amongst the group, and whether they developed alternative plans to account for uncertain scientific situations. The implications of the findings for emergency manager use, understanding and utilisation of scientific information are discussed.
Haruo HAYASHI1, Fumihiko IMAMURA2, Yuichi ONO2, Masayoshi NAKASHIMA1 and Keiko TAMURA3
- Disaster Prevention Research Institute, Kyoto University, Uji, Kyoto, Japan
- International Research Institute of Disaster Science, Tohoku University, Sendai, Miyagi, Japan
- Emergency Management Office, Niigata University, Niigata, Japan
The Japanese IRDR National Committee is currently preparing a proposal for a new discipline of science titled toward disaster risk reduction by design. It consists of five components: assessment of multi-hazard risks, monitoring exposure and vulnerability, linking disaster risk reduction and economic growth, behavioural disaster management, and data integration and information fusion.
Even though many natural and social scientific research have been conducted for disaster reduction, the damage and losses due to natural disasters still continue to increase in both developed and developing countries.
The purpose of this study is to promote multi-disciplinary research for reducing disaster risk and curbing losses by establishing a new discipline called “Behavioural Disaster Management” to improve disaster resilience as an attempt to contribute to the promotion of the “RIA” programme under IRDR.
Just like behavioural medicine in the 1980s, and behavioural economics in 2000s, behavioural disaster management explores first knowledge-based human actions by understanding human decision-making process based on “bounded rationality” in the context of disaster mitigation, preparedness, response and recovery, which then will be integrated with the achievements from other established domains of disaster research using web-based GIS.
Five research themes will be focused in this study:
- Development of a quantitative behavioural and attitudinal measurement system to evaluate whether people may or can take appropriate safety actions;
- Development of a standardised incident response system, which takes into account decision-making processes based on both bounded rationality and cultural constraints;
- Development of standard operation procedures to coordinate incident response of relevant organisations;
- Development of an effective risk and crisis communication system among various stakeholders; and
- Development of a theory of long-term disaster recovery and human sustainability.
Frank SCHÄTTER, Marcus WIENS and Frank SCHULTMANN
Institute for Industrial Production (IIP), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Consequences of climate change, in combination with social trends such as urbanisation and population growth, have led to a higher vulnerability of the society coping with an increased number of natural disasters. A main focus of disaster management is the maintenance of humanitarian relief supply networks (SNs), which are targeted at delivering the right relief items in time to all people in need during a disaster. Therefore, proactive risk reduction measures are essential to improve logistic operations or critical infrastructure in vulnerable regions in advance, i.e improving the stability and quality of the transport infrastructure. Strategic decision support plays an important role in humanitarian logistics. A prominent example is the facility location problem that aims at identifying optimal locations such as tent hospitals to serve injured people. Particularly in the early phases of the disaster, decisions are needed quickly and under a high pressure for the decision-makers by knowing that the decision may have consequences on all future decisions. Proactive risk reduction may be helpful to provide decision-makers with optimal strategies in advance. However, disasters are faced by severe uncertainty and complexity, limited knowledge about the causes of the disaster and characterized by a continuous change of the situation in unpredicted ways. Following these assumptions, we believe that adequate proactive risk reduction measures are not practical. We propose to strengthen the focus on ad-hoc decision support to capture information in almost real-time and processing information efficiently to reveal uncertainties that have not been predicted so far. Therefore, we present an ad-hoc decision support system, which uses scenario techniques to specify uncertainties into future developments of the situation and an optimisation model to compute promising decision options. By combining these aspects in a dynamical manner and integrating new information continuously, uncertainties are revealed to ensure that a decision is always based on the best currently available and processed information. To filter robust decision options, methods of multi-attribute decision-making (MADM) are applied. Our approach is illustrated by a disaster decision-making situation that aims at designing efficient and effective humanitarian relief SNs after the Haiti earthquake 2010.