2020 Vol. 11, No. 3

Display Method:
Potential Linkages Between Social Capital, Flood Risk Perceptions, and Self-Efficacy
Paul Hudson, Liselotte Hagedoorn, Philip Bubeck
2020, 11(3): 251-262. doi: 10.1007/s13753-020-00259-w
A growing focus is being placed on both individuals and communities to adapt to flooding as part of the Sendai Framework for Disaster Risk Reduction 2015–2030. Adaptation to flooding requires sufficient social capital (linkages between members of society), risk perceptions (understanding of risk), and self-efficacy (selfperceived ability to limit disaster impacts) to be effective. However, there is limited understanding of how social capital, risk perceptions, and self-efficacy interact. We seek to explore how social capital interacts with variables known to increase the likelihood of successful adaptation. To study these linkages we analyze survey data of 1010 respondents across two communities in Thua Tien-Hue Province in central Vietnam, using ordered probit models. We find positive correlations between social capital, risk perceptions, and self-efficacy overall. This is a partly contrary finding to what was found in previous studies linking these concepts in Europe, which may be a result from the difference in risk context. The absence of an overall negative exchange between these factors has positive implications for proactive flood risk adaptation.
Barriers to Insurance as a Flood Risk Management Tool: Evidence from a Survey of Property Owners
Jason Thistlethwaite, Daniel Henstra, Craig Brown, Daniel Scott
2020, 11(3): 263-273. doi: 10.1007/s13753-020-00272-z
By using risk-adjusted price signals to transfer responsibility for property-level flood protection and recovery from governments to property owners, flood insurance represents a key tenet of the flood risk management (FRM) paradigm. The Government of Canada has worked with insurers to introduce flood insurance for the first time as a part of a broader shift towards FRM to limit the growing costs of flooding. The viability of flood insurance in Canada, however, has been questioned by research that disputes the utility of purchasing coverage by property owners. This study tested this assumption by drawing on public opinion survey data to assess factors that influence decisions about the utility of insurance. The findings reveal that Canadians have limited knowledge of flood insurance coverage, exhibit a low willingness-to-pay for both insurance and property-level flood protection measures, and expect governments to shoulder much of the financial burden of flood recovery through disaster assistance.
Evacuating a First Nation Due to Wildfire Smoke: The Case of Dene Tha’ First Nation
Kyla D. Mottershead, Tara K. McGee, Amy Christianson
2020, 11(3): 274-286. doi: 10.1007/s13753-020-00281-y
Almost every year, First Nations are evacuated in Canada because of wildfire proximity and smoke. Dynamics of wildfires, and remote locations, unique sociocultural characteristics, and limited emergency management resources present challenges for evacuation organizers and residents. This study explores how Dene Tha' First Nation evacuated their Taché community in July 2012 due to wildfire smoke and how the evacuation process affected evacuees. Interviews were completed with 31 evacuation organizers and residents to examine the factors that helped and hindered the evacuation process. Lack of information about the nearby wildfire, smoke, and evacuation of the nearby small community of Zama City, combined with a generic evacuation plan, delayed and posed challenges during the evacuation of this Dene Tha' community. Strong leadership and its role in community organizing, keeping families together, providing the social support they needed, and using familiar host communities, demonstrated and contributed to the community's resilience during the evacuation. Measures to improve evacuations and emergency management in the community and other First Nations in Canada are identified and discussed.
Remembering, Forgetting, and Absencing Disasters in the Post-disaster Recovery Process
Charlotte Monteil, Jenni Barclay, Anna Hicks
2020, 11(3): 287-299. doi: 10.1007/s13753-020-00277-8
Sustainable post-disaster recovery implies learning from past experience in order to prevent recreating forms of vulnerability. Memory construction supports both the healing process and redevelopment plans. Hence, memory of disaster results from the balance between remembering, forgetting, and absencing elements of the disaster, and can be both a tool and an obstacle to sustainable recovery. We explore here how collective memory is built in a post-disaster context to respond to the needs of this critical period, and how it shapes recovery. This ethnographic study, conducted between 2015 and 2017, explores the recovery processes in Montserrat, a small Caribbean island affected by an extended volcanic crisis from 1995 to 2010. Although this study does not give tangible solutions for disaster risk reduction in a post-disaster context, it highlights potential obstacles for learning from a disaster and how they may be surmounted. We argue that it is crucial to acknowledge evolving collective memory in order to implement effective measures for preserving and sharing a shared understanding of disaster across generations and social groups in a way that supports disaster risk awareness. We also maintain that acknowledging the dilemma faced by authorities and disaster management agencies during a period of conflicting needs may encourage the reconsideration of risk framing, and hence reveal how to improve implementation of disaster risk reduction measures.
Evaluation of Fire Service Command Unit Trainings
Meinald T. Thielsch, Dzenita Hadzihalilovic
2020, 11(3): 300-315. doi: 10.1007/s13753-020-00279-6
The lack of routine and training of command units and emergency managers is among the main causes of suboptimal decisions and could lead to serious consequences. To ensure optimal standards of emergency management training, specific and valid evaluation tools are needed—but are lacking. Thus, the present study's purpose is to validate instruments for the evaluation of tactical and strategic leader trainings, in particular command unit trainings, based on survey data of n=288 German Command Unit members. Resulting questionnaires were named “FIRE-CU” (Feedback Instrument for Rescue forces Education – Command Unit) and “FIRE-CPX” (Feedback Instrument for Rescue forces Education – Command Post eXercise scale). Results of confirmatory factor analyses show a good fit for the postulated four-dimensional structure of process scales in the FIRE-CU (trainer's behavior, structure, overextension, group), for the two-dimensional structure of outcome scales in the FIRE-CU (self-rated competence, transfer), and for the one-dimensional structure of the FIRE-CPX. Further, strong evidence is found for reliability as well as for convergent, divergent, and concurrent validity of both the FIRE-CU and FIRE-CPX. Implications for research and practical application are also discussed to enable broad applicability in various educational programs for public security and crisis management.
The Challenging Place of Natural Hazards in Disaster Risk Reduction Conceptual Models: Insights from Central Africa and the European Alps
Caroline Michellier, Patrick Pigeon, André Paillet, Théodore Trefon, Olivier Dewitte, François Kervyn
2020, 11(3): 316-332. doi: 10.1007/s13753-020-00273-y
Based on a literature review and two case studies, this article presents the difficulties inherent in the main disaster risk reduction conceptual models. The method used to highlight such evidence is to compare two programs on disaster risk reduction with mainstream conceptual models. The authors participated in these programs, which were confronted with the need to integrate contributions and insights from both earth and social sciences. Our analysis found that the existing main conceptual models were unable to do justice to disaster risk reduction needs. This finding encouraged us to critique these models. Further effort led us to present possible solutions to compensate for the shortcomings of current models while taking into account the contextualization and dynamics of phenomena, as well as grappling with the more explicit integration of hazards and hazard risk into model design.
Conceptualizing Individual and Household Disaster Preparedness: The Perspective from Cameroon
Emmanuel Nzengung Nojang, Jessica Jensen
2020, 11(3): 333-346. doi: 10.1007/s13753-020-00258-x
This research explored the basic issue of what preparedness means and entails to people in Fako Division, Cameroon—a place threated by many hazards and that has experienced many disasters. Findings from the analysis of the 33 interviews conducted in this study indicate that preparedness is a dynamic state of readiness that is dependent on context, a social process, and a process of completing activities to save lives and minimize the effects of disasters. In addition, the research determined that Cameroonians view a wholly prepared person as someone who would: (1) have knowledge about hazards and what to do about them; (2) engage others, including their families and neighbors, in discussions about activities related to hazards; and (3) participate in activities to minimize loss from hazards, sustain themselves in the face of hazards, and flee from hazards. The findings from the interview data synchronize to a large extent with what is implied, but not clearly stated, in the existing research literature. The article addresses this synchrony, posits a definition of preparedness, and identifies the theoretical components of preparedness.
Quantitative Risk Analysis of a Rainfall-Induced Complex Landslide in Wanzhou County, Three Gorges Reservoir, China
Lili Xiao, Jiajia Wang, Yanbo Zhu, Jun Zhang
2020, 11(3): 347-363. doi: 10.1007/s13753-020-00257-y
On 4 April 2013, a 1.5 million cubic meter landslide occurred in Sunjia Town, Wanzhou County, Three Gorges Reservoir, China. After initiation, the Sunjia landslide traveled about 30 m toward the northeast and destroyed most of the infrastructure in its path. The landslide was triggered by heavy rainfall and previous slope excavations, but this slope also displayed a complicated failure process: the overlying earth slope first deformed and then induced sliding along underlying rock surfaces. Surface displacements that resulted from continuous creeping of the post-event slope were observed by an emergency monitoring system that revealed the disequilibrium state of the slope. To discuss the stability and future movements of the remaining unstable debris deposits, we developed a geotechnical model of the post-slide slope, calculated how it can slide again in an extreme rainfall scenario, and estimated the potential runout distance using the Tsunami Squares method. We then estimated the number of people and the value of the infrastructure threatened by this potential landslide. Lastly, we analyzed the vulnerability of elements at risk and quantitatively evaluated the hazard risk associated with the most dangerous scenario. This quantitative risk analysis provides a better understanding of, and technical routes for, hazard mitigation of rainfall-induced complex landslides.
Mass-Casualty Distribution for Emergency Healthcare: A Simulation Analysis
Mohsin Nasir Jat, Raza Ali Rafique
2020, 11(3): 364-377. doi: 10.1007/s13753-020-00260-3
This study focuses on the casualty-load distribution problem that arises when a mass casualty incident (MCI) necessitates the engagement of multiple medical facilities. Employing discrete event simulations, the study analyzed different MCI response regimes in Lahore, Pakistan, that vary in terms of the level of casualty-load distribution and the required coordination between the incident site and the responding hospitals. Past terrorist attacks in this major metropolitan area were considered to set up experiments for comparing delays in treatment under the modeled regimes. The analysis highlights that the number of casualties that are allowed to queue up at the nearest hospital before diverting the casualty traffic to an alternate hospital can be an important factor in reducing the overall treatment delays. Prematurely diverting the casualty traffic from the incident site to an alternate hospital can increase the travel time, while a delay in diversion can overload the nearest hospital, which can lead to overall longer waiting times in the queue. The casualty distribution mechanisms based only on the responding hospitals' available capacity and current load can perform inefficiently because they overlook the trade-off between the times casualties spend in traveling and in queues.
Dynamic Spatio-Temporal Tweet Mining for Event Detection: A Case Study of Hurricane Florence
Mahdi Farnaghi, Zeinab Ghaemi, Ali Mansourian
2020, 11(3): 378-393. doi: 10.1007/s13753-020-00280-z
Extracting information about emerging events in large study areas through spatiotemporal and textual analysis of geotagged tweets provides the possibility of monitoring the current state of a disaster. This study proposes dynamic spatio-temporal tweet mining as a method for dynamic event extraction from geotagged tweets in large study areas. It introduces the use of a modified version of ordering points to identify the clustering structure to address the intrinsic heterogeneity of Twitter data. To precisely calculate the textual similarity, three state-of-the-art text embedding methods of Word2vec, GloVe, and FastText were used to capture both syntactic and semantic similarities. The impact of selected embedding algorithms on the quality of the outputs was studied. Different combinations of spatial and temporal distances with the textual similarity measure were investigated to improve the event detection outcomes. The proposed method was applied to a case study related to 2018 Hurricane Florence. The method was able to precisely identify events of varied sizes and densities before, during, and after the hurricane. The feasibility of the proposed method was qualitatively evaluated using the Silhouette coefficient and qualitatively discussed. The proposed method was also compared to an implementation based on the standard density-based spatial clustering of applications with noise algorithm, where it showed more promising results.
Reviewing the Oceanic Niño Index (ONI) to Enhance Societal Readiness for El Niño's Impacts
Michael H. Glantz, Ivan J. Ramirez
2020, 11(3): 394-403. doi: 10.1007/s13753-020-00275-w
NOAA's Oceanic Niño Index (ONI) is used to record for historical purposes the occurrence and duration of El Niño episodes, based on the monitoring of sea surface temperatures (SSTs) in the central Pacific Ocean. The ONI is used to identify the onset of an above average SST threshold that persists for several months, encompassing both the beginning and end of an El Niño episode. The first appearance of an anomalous seasonal value of 0.5 ℃ suggests with a high probability that an El Niño could emerge, but for heightened warnings, one must wait for several months. In this article, we proposed that the ONI value of 0.7 ℃ identifies a tipping point at which the El Niño event becomes locked in, which can provide additional lead time for mitigative actions to be taken by societal decision makers. Our preliminary findings suggest that a first appearance of 0.7 ℃ value could serve as a credible marker of El Niño's locked-in phase, which can provide additional credibility to the current 0.5 ℃ El Niño onset indicator for at-risk societies to get ready for El Niño's foreseeable societal and ecological impacts.
A Likert Scale-Based Model for Benchmarking Operational Capacity, Organizational Resilience, and Disaster Risk Reduction
Gianluca Pescaroli, Omar Velazquez, Irasema Alcántara-Ayala, Carmine Galasso, Patty Kostkova, David Alexander
2020, 11(3): 404-409. doi: 10.1007/s13753-020-00276-9
Likert scales are a common methodological tool for data collection used in quantitative or mixed-method approaches in multiple domains. They are often employed in surveys or questionnaires, for benchmarking answers in the fields of disaster risk reduction, business continuity management, and organizational resilience. However, both scholars and practitioners may lack a simple scale of reference to assure consistency across disciplinary fields. This article introduces a simple-to-use rating tool that can be used for benchmarking responses in questionnaires, for example, for assessing disaster risk reduction, gaps in operational capacity, and organizational resilience. We aim, in particular, to support applications in contexts in which the target groups, due to cultural, social, or political reasons, may be unsuitable for in-depth analyses that use, for example, scales from 1 to 7 or from 1 to 10. This methodology is derived from the needs emerged in our recent fieldwork on interdisciplinary projects and from dialogue with the stakeholders involved. The output is a replicable scale from 0 to 3 presented in a table that includes category labels with qualitative attributes and descriptive equivalents to be used in the formulation of model answers. These include examples of levels of resilience, capacity, and gaps. They are connected to other tools that could be used for in-depth analysis. The advantage of our Likert scale-based response model is that it can be applied in a wide variety of disciplines, from social science to engineering.