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How risk is defined, the nature of methodologies used to assess risk, and the degree to which rare events should be included in a disaster risk analysis, are important considerations when developing policies, programs and priorities to manage risk. Each of these factors can significantly affect risk estimation. In Part 1 of this paper [Etkin, D. A., A. A. Mamuji, and L. Clarke. 2018. "Disaster Risk Analysis Part 1: The Importance of Including Rare Events." Journal of Homeland Security and Emergency Management.] we concluded that excluding rare events has the potential to seriously underestimate the cumulative risk from all possible events, For example, of the 100 most expensive weather disasters in the US, the single most expensive event accounts for 16% of total economic impacts. Similarly, the worst explosion disaster accounts for 17% of the fatalities of the total 100 worst events. though including them can be very challenging both from a methodological and data availability perspective. Underestimating risk can result in flawed disaster risk reduction policies, resulting in insufficient attention being devoted to mitigation and/or prevention. In Part 2, we survey various governmental emergency management policies and methodologies in order to evaluate varying equations used to define risk, and to assess potential biases within disaster risk analyses that do comparative risk ranking. We find (1) that the equations used to define risk used by emergency management organizations are frequently less robust than they should or are able to be, and (2) that methodologies used to assess risk are often inadequate to properly account for the potential contribution of rare events. We conclude that there is a systemic bias within many emergency management organizations that results in underestimation of risk. [ABSTRACT FROM AUTHOR]

Rare events or worst-case scenarios are often excluded from disaster risk analysis. Their inclusion can be very challenging, both from methodological and data availability perspectives. We argue that despite these challenges, not including worst-case scenarios in disaster risk analysis seriously underestimates total risk. It is well known that disaster data sets generally have fat tails. In this paper we analyze data for a number of disaster types in order to empirically examine the relative importance of the few most damaging events. The data show consistent fat-tail trends, which suggests that rare events are important to include in a disaster risk analysis given their percentage contributions to cumulative damage. An example of biased risk estimation is demonstrated by a case study of risk analysis of tanker spills off the western coast of Canada. Incorporating worst-case scenarios into disaster risk analysis both reduces the likelihood of developing fantasy planning documents, and has numerous benefits as evidenced by applications of foresight analysis in the public sector. A separate paper "Disaster Risk Analysis Part 2" explores how disaster risk analyses are operationalized in governmental emergency management organizations, and finds evidence of a systemic underestimation of risk. [ABSTRACT FROM AUTHOR]

Purpose – The present study seeks to explore the minds and thoughts of emergency management professionals in Ontario in order to better understand the institution, and engage them in a renewed dialogue with communities, academia and other stakeholders. The intention is to strengthen the institution of emergency management, which is the foundation of disaster mitigation. Design/methodology/approach – The study is based on interviews conducted with emergency management professionals from the public, private and non-governmental organization (NGO) sectors in the Province of Ontario, Canada. The questions were a combination of structured and open-ended questions to elicit rich details on emergency management professionals' views. Analysis of interview transcriptions highlighted the attitudes and perceptions of the interviewees with respect to themselves, their own organizations, their role in emergency management, and their jurisdictions. The study also provided an opportunity for respondents to provide examples or comments to illustrate their responses. A total of 43 interviews have been analyzed for this paper. Findings – The research objective of enhancing the understanding of the institution of emergency management through the minds of emergency management professionals in Ontario has been successfully achieved. It is clear that emergency managers and other professionals engaged in consulting, response and humanitarian assistance activities realize their role and responsibilities quite well. The majority of participants felt that politics and a lack of understanding of one anothers' roles often limit progress. A clear consensus regarding engaging community players in the development of mitigation strategies and resource allocation emerged in this study. Originality/value – The research conducted is the first of its kind in the province of Ontario in Canada. With the help of personal interviews and survey questionnaire, a better understanding of the emergency management institution and professionals working in this field could be realized. [ABSTRACT FROM AUTHOR]

This paper explores two issues that have been receiving increasing attention in recent decades, climate change adaptation and natural disaster risk reduction. An examination of the similarities and differences between them reveals important linkages but also significant differences, including the spectrum of threats, time and spatial scales, the importance of local versus global processes, how risks are perceived, and degree of uncertainty. Using a risk perspective to analyze these issues, preferential strategies emerge related to choices of being proactive, reactive, or emphasizing risk management as opposed to the precautionary principle. The policy implications of this analysis are then explored, using Canada as a case study. [ABSTRACT FROM AUTHOR]

Creating effective disaster and emergency management programs can be an enormously challenging task because of the many difficulties and barriers that present themselves to people and institutions working in this field. The present study addresses two main concerns: (1) what barriers exist within Canadian society to effective disaster risk reduction from the perspective of the emergency management community and (2) what barriers exist within the Canadian emergency management community to effective disaster risk reduction, both from a cultural and institutional perspective? We conducted interviews with emergency management professionals from the public and private sectors as well as some NGOs in order to ascertain their opinions and perspectives with respect to these questions. The results have been analyzed and discussed in this paper. [ABSTRACT FROM AUTHOR]

The article discusses the impacts of human behavior on mitigating natural disasters particularly in Canada. It is important to consider that human decisions have evidential consequences relating to the things that surround him, and that every individual must not separate disaster prevention from his/her ethics, culture, or the broader social and environmental systems that sustain him. In presenting mitigation of disaster issues, the author emphasizes the interconnectedness between humans and nature, and how a dysfunctional relationship can contribute towards vulnerability to such calamities. It has also been pointed out that mitigation is defined as sustained actions to reduce or eliminate the long-term impacts and risks associated with natural and human-induced disasters.

To study the impact of incremental climatic warming on summer extreme temperature event frequency, the historical record of daily maximum June, July, and August temperatures was analyzed for nine sites across Canada. It was found that all of these sites are well modeled by a first-order autoregressive process using three parameters: the mean, variance, and first-order autocorrelation coefficient. For slight changes in the mean or variance there are increases in the frequency of both single days and runs of 2--5 consecutive days with daily maximum temperatures over a threshold value. For example, for a 38C increase in the mean daily maximum temperature at Toronto, the frequency of a 5-day consecutive run over 308C rose by over a factor of 8 to 7.1%. Sites with less variability are more sensitive to an increase in the mean summer temperature than sites with higher variability. Analysis of simulated series indicates that when two parameter values change simultaneously the change in the frequency of a given event is usually greater than the sum of the individual changes. Output from the Canadian Climate Centre GCMII model for the nine sites for both the current and 2 3 CO2 atmosphere indicate an average increase in the daily maximum temperature of 4.28C. Changes in the standard deviation and autocorrelation were usually less pronounced. For Toronto, a positive correlation (R 2 5 0.718) between daily peak power demand and the cube of the current and previous 2 days daily maximum temperature was found. A sensitivity analysis was performed on daily peak power demand by first generating temperature time series and then using the derived regression relationship. Results follow a predictable pattern and indicate that the standard deviation of the peak power series increases proportionally more than the mean for increases in the mean daily maximum temperature. For example, for a 38C increase in mean daily maximum temperature, the increase in mean peak... [ABSTRACT FROM AUTHOR]

Purpose: The plethora of contributions to social learning has resulted in a wide range of interpretations, meanings and applications of social learning, both within and across disciplines. However, advancing the concept and using social learning methods and tools in areas like disaster-shocks requires interdisciplinary consolidation of understandings. In this context, the primary focus of this paper is on the contributions of social learning to disaster risk reduction (DRR). Design/methodology/approach: By applying a three-round policy Delphi process involving 18 purposefully selected scholars and expert-practitioners, the authors collected data on the meanings of social learning for two groups of professionals, DRR and social-ecological resilience. The survey instruments included questions relating to the identification of the core elements of social learning and the prospects for enhancing social-ecological resilience. Findings: The results revealed strong agreement that (1) the core elements of social learning indicate a collective, iterative and collaborative process that involves sharing/networking, changes in attitudes and knowledge and inclusivity; (2) social learning from disasters is unique; and (3) linkages between disciplines can be built by promoting interdisciplinarity, networks and knowledge platforms; collaboration and coordination at all levels; and teaching and practicing trust and respect. Social learning is useful in preparing for and responding to specific disaster events through communication; sharing experience, ideas and resources; creating synergies for collective action and promoting resilience. Research limitations/implications: The policy Delphi process involved a limited number of participants to control the quality of the data. To the best of the authors' knowledge, this paper is the first of its kind to identify the core elements of social learning, specifically, in the disaster-shock context. It also makes significant contributions to the interdisciplinary integration issues. Practical implications: The practical implications of this study are related to pre-disaster planning and mitigation through the application of social learning on disaster-shocks. Social implications: The social implications of this study are related to valuing social learning for the improvement of disaster planning, management, and policy formulation and implementation in reducing disaster risks. Originality/value: The study provides a consensus view on the core elements of social learning and its role in DRR and resilience building. Relevant to all stages of DRR, social learning is best characterized as a collective, iterative and collaborative process. It can be promoted by enhancing networking and interdisciplinarity. [ABSTRACT FROM AUTHOR]

Focuses on the Canadian ice storm of 1998 and on how communities formed to find solutions to pressing problems. Humans' vulnerability to natural disasters; Socioeconomic impact of the ice storm; Meteorological aspects; Affected sectors; Impact on the agricultural industry.