2016 Vol. 7, No. 2

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Social Vulnerability to Natural Hazards in Brazil
Beatriz Maria de Loyola Hummell, Susan L. Cutter, Christopher T. Emrich
2016, 7(2): 111-122. doi: 10.1007/s13753-016-0090-9
Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country. Social vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index (SoVI®) replication study for Brazil and shows how SoVI® concepts and indicators were adapted to the country. SoVI® Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis (PCA), 45 city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast regions. The least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.
Government Investment in Disaster Risk Reduction Based on a Probabilistic Risk Model: A Case Study of Typhoon Disasters in Shenzhen, China
Tao Ye, Yao Wang, Binxia Wu, Peijun Shi, Ming Wang, Xiaobing Hu
2016, 7(2): 123-137. doi: 10.1007/s13753-016-0092-7
In recent years, cost-benefit analysis (CBA) has played an important role in disaster risk reduction (DRR) investment decisions, and now increasing attention is being paid to its application in developing countries. This article discusses government investment choices in DRR against typhoon disasters in Shenzhen, China. While the existing literature mainly focuses on disaster mitigation measures such as structural retrofitting, this study proposes a holistic framework of DRR investments in which structural (windproof retrofitting) and financial (insurance premium subsidies and post-disaster relief) are all taken into account. In particular, intermeasure spillover effects are measured and used in CBA. The results show that insurance premium subsidies yield the highest benefit-cost ratio and should be prioritized in investment. Windproof retrofitting comes in second place in terms of the benefit-cost ratio and can be considered when there is a sufficient budget. These results further confirm the need of a holistic review of government DRR investments to derive policy recommendations, while challenges remain in relation to the probabilistic modeling capacity to support CBA.
A New Method for Resource Allocation Optimization in Disaster Reduction and Risk Governance
Xiao-Bing Hu, Ming Wang, Tao Ye, Peijun Shi
2016, 7(2): 138-150. doi: 10.1007/s13753-016-0089-2
How to allocate and use resources play a crucial role in disaster reduction and risk governance (DRRG). The challenge comes largely from two aspects: the resources available for allocation are usually limited in quantity; and the multiple stakeholders involved in DRRG often have conflicting interests in the allocation of these limited resources. Therefore resource allocation in DRRG can be formulated as a constrained multiobjective optimization problem (MOOP). The Pareto front is a key concept in resolving a MOOP, and it is associated with the complete set of optimal solutions. However, most existing methods for solving a MOOPs only calculate a part or an approximation of the Pareto front, and thus can hardly provide the most effective or accurate support to decision-makers in DRRG. This article introduces a new method whose goal is to find the complete Pareto front that resolves the resource allocation optimization problem in DRRG. The theoretical conditions needed to guarantee finding a complete Pareto front are given and a practicable, ripple-spreading algorithm is developed to calculate the complete Pareto front. A resource allocation problem of risk governance in agriculture is then used as a case study to test the applicability and reliability of the proposed method. The results demonstrate the advantages of the proposed method in terms of both solution quality and computational efficiency when compared with traditional methods.
The Sustainable Procedure Framework for Disaster Risk Management: Illustrated by the Case of the EU Floods Directive in Sweden
Beatrice Hedelin
2016, 7(2): 151-162. doi: 10.1007/s13753-016-0093-6
How can the concrete meaning of the ambiguous and theoretical concept of sustainable development (SD) be defined and implemented, without losing sight of its fundamental principles? This study introduces a theoretical framework that supports studies of SD implementation in the context of strategic disaster risk management, by defining what SD implies with regard to planning procedures. The framework is based on the procedural SD principles of participation and integration. It was originally developed for, and has shown great value in, the field of water resource management. In-depth interviews with senior risk management researchers indicate that the framework is also applicable to and valuable for disaster risk management studies. To illustrate the application of the framework, a study of the EU Floods Directive in Sweden is summarized with the framework as the basis for the analysis.
From Top-Down to “Community-Centric” Approaches to Early Warning Systems: Exploring Pathways to Improve Disaster Risk Reduction Through Community Participation
Marie-Ange Baudoin, Sarah Henly-Shepard, Nishara Fernando, Asha Sitati, Zinta Zommers
2016, 7(2): 163-174. doi: 10.1007/s13753-016-0085-6
Natural hazards and their related impacts can have powerful implications for humanity, particularly communities with deep reliance on natural resources. The development of effective early warning systems (EWS) can contribute to reducing natural hazard impacts on communities by improving risk reduction strategies and activities. However, current shortcomings in the conception and applications of EWS undermine risk reduction at the grassroots level. This article explores various pathways to involve local communities in EWS from top-down to more participatory approaches. Based on a literature review and three case studies that outline various levels of participation in EWS in Kenya, Hawai'i, and Sri Lanka, the article suggests a need to review the way EWS are designed and applied, promoting a shift from the traditional expert-driven approach to one that is embedded at the grassroots level and driven by the vulnerable communities. Such a community-centric approach also raises multiple challenges linked to a necessary shift of conception of EWS and highlights the need for more research on pathways for sustainable community engagement.
Charting Disaster Recovery via Google Street View: A Social Science Perspective on Challenges Raised by the Fukushima Nuclear Disaster
Leslie Mabon
2016, 7(2): 175-185. doi: 10.1007/s13753-016-0087-4
There is increasing interest in using Google Street View (GSV) for research purposes, particularly with regard to “virtually auditing” the built environment to assess environmental quality. Research in this field to date generally suggests GSV is a reliable means of understanding the “real world” environment. But limitations around the dates and resolution of images have been identified. An emerging strand within this literature is also concerned with the potential of GSV to understand recovery post-disaster. Using the GSV data set for the evacuated area around the Fukushima Dai’ichi nuclear power plant as a case study, this article evaluates GSV as a means of assessing disaster recovery in a dynamic situation with remaining uncertainty and a significant value and emotive dimension. The article suggests that GSV does have value in giving a high-level overview of the post-disaster situation and has potential to track recovery and resettlement over time. Drawing on social science literature relating to Fukushima, and disasters more widely, the article also argues it is imperative for researchers using GSV to reflect carefully on the wider socio-cultural contexts that are often not represented in the photo montage.
Territorial Accessibility and Decision-Making Structure Related to Debris Flow Impacts on Roads in the French Alps
Marina Utasse, Vincent Jomelli, Delphine Grancher, Frederic Leone, Daniel Brunstein, Clement Virmoux
2016, 7(2): 186-197. doi: 10.1007/s13753-016-0088-3
The Alps are highly impacted by debris flows that cause major problems for companies and transport networks located in the valley bottoms. One such event occurred in the Rif Blanc catchment and affected the road network in the French Alps, as well as adjacent areas across the Italian border, for several days in June 2012. This article presents two independent approaches to vulnerability assessment. Based on investigations conducted during a survey of local authorities following the event, we compared theoretical risk management and real crisis management in terms of decision making and modes of intervention. Functional vulnerability and territorial consequences were analyzed using a best travel time model of accessibility. We show that a bottom-up approach is practiced in case of actual management planning with a central coordination of general council. Conversely theoretical crisis management shows prefect as the key actor supported by several other state institutions. Our analysis also revealed that a debris flow event with a local impact on the road network has territorial consequences at a regional scale. This study contributes to the discussion about how to minimize the vulnerability of alpine transport networks prone to debris flows. Our results could serve as a decision support tool for public authorities.
Technologies to Support Community Flood Disaster Risk Reduction
Ian McCallum, Wei Liu, Linda See, Reinhard Mechler, Adriana Keating, Stefan Hochrainer-Stigler, Junko Mochizuki, Steffen Fritz, Sumit Dugar, Miguel Arestegui, Michael Szoenyi, Juan-Carlos Laso Bayas, Peter Burek, Adam French, Inian Moorthy
2016, 7(2): 198-204. doi: 10.1007/s13753-016-0086-5
Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge.