Hazards Governance Learning and Overview Essay

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Module 4 Learning and Overview

Hello CPP 510 students -- welcome to Module 4

Okay – we’re at the midpoint of the term and it’s time for a quick summary – which we will cover in the module intro lecture. But briefly, so far we have tackled the overarching topic of hazards governance, considered its relationship to disaster science, and then what it means to think about the production of risk reduction and community resilience as complex public goods.

Here, in this module, we will delve into central concepts of risk – which we have, of course, discussed…but have no yet treated to more specific scrutiny. As a result, Module 4. Risk and Risk Management: Basic Concepts; Risk Management from Policy, Organizational & Operational Perspectives will address what we mean when we use terms such as risk, risk reduction, risk management – and other key concepts/terms such as vulnerability and moral hazard.

The purpose and value of covering risk as a stand-along topic is straightforward: it is central to understanding how we collectively and individually attempt to deal with hazards, whether those hazards are natural, biologic, technological, or intentional human acts, e.g. acts of terrorism. Thinking about risk and how to assess it is essential to effective practices in the emergency management and homeland security domains – and thus is also central to understanding hazards governance.

The module learning objectives are listed below, as are lecture slides and videos and downloadable files of this module’s assigned reading materials. The link to the Learning Module 4 assignment provides all necessary details.

The learning objectives for Module 4 are as follows. By the conclusion of this module, students will be able to:

  • Identify and define core concepts of risk, risk management and disaster risk reduction
  • Utilize the concepts of risk and risk management in assessing how governments seek to reduce risk and promote resilience
  • Understand how the concept of social vulnerability to hazards and risk relates to disaster risk reduction and risk management in general
  • Identify and understand how applied practices related to reduction of risk and promotion of resilience function in practice, in particular settings, such as urban communities

For this learning module, please study the following materials. You will need to understand the concepts presented here to complete the assignments.

Learning Module 4 Assigned Readings


Additional reading (not required -- but useful supplemental material)

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The purpose of the assigned written work in this course is threefold: (1) the assignments and written exam afford students the opportunity to demonstrate substantive understanding of materials covered in course readings, lectures and online discussion, (2) the assignments and exam permit students to develop and demonstrate research, analytic and written communication skills, and (3) the written work permits the instructor to assess student knowledge, skills and ability within this subject domain. This reaction essay to the assigned reading materials in Learning Module 4 is explicitly intended to meet the objectives stated above. For this written assignment, please address one of the three questions posed below. Please indicate clearly which reaction question you are responding to at the top of your document (Option A, B or C). The Reaction Essay must be between 1,500 to 2,000 words. Please do not include an abstract. Use the American Psychological Association (APA) method of citing references. Check out Purdue University’s Online Writing Lab (Links to an external site.) which is a very useful website that explains the APA citation method, with lots of clear illustrations. The APA website (Links to an external site.)includes PDFs and video tutorials to learn and apply APA formatting. 4 Rules for successful (and correct) references: 1. Avoid long direct quotes. You are supposed to make the argument. The quote is merely there to support your argument, not make the argument for you. 2. Quotes require quotation marks. A verbatim quote without quotation marks is plagiarism. 3. Use in-text citations. Don't waste your time spelling out article types, titles, or authors. In-text citations are there so you can get directly to the point. For example, Meyer (2020) states that... 4. In-text citations come in pairs. Every in-text citation needs an end reference that fully details author name(s), article/book title, year of publication, journal names, etc. With the above instructions in mind, please answer one of the following three questions: Essay Question A: IRGC (2018) provides a general framework aimed at explication of effective governance around risk and risk management -- with a unique emphasis on the idea of systemic risks. In your response to this question, please explain what the report means by the concept of systemic risk, what it identifies as key governance practices for systemic risks, and finally, offer your own view of possible strengths or weaknesses of the process/framework the report outlines. Essay Question B: Kuhlicke (2020) provides a very helpful overview of what risk-based management approaches are in the context of natural hazards. For this question option, please explain how Kuhlicke defines a risk-based management approach and more specifically, how resilience can be incorporated in such an approach. Please offer your own assessment of the strengths or weaknesses of Kuhlicke's presentation, such as whether you agree or disagree with his somewhat critical view of conventional understandings of DRR. Essay Question C: Alexander (2013) provides a broad overview of the concept of resilience -- how it has changed over time, how it has been used in different ways, and what it means to the idea of disaster risk reduction (DRR). Please summarize Alexander's assessment of the resilience concept, and provide your own assessment of how effectively resilience principles can or should be incorporated in DRR practices. Please be precise when explaining how DRR practices should function in applied practice or operations. Climatic Change (2015) 133:53–68 DOI 10.1007/s10584-013-0913-2 Scenarios for vulnerability: opportunities and constraints in the context of climate change and disaster risk Joern Birkmann & Susan L. Cutter & Dale S. Rothman & Torsten Welle & Matthias Garschagen & Bas van Ruijven & Brian O’Neill & Benjamin L. Preston & Stefan Kienberger & Omar D. Cardona & Tiodora Siagian & Deny Hidayati & Neysa Setiadi & Claudia R. Binder & Barry Hughes & Roger Pulwarty Received: 31 January 2013 / Accepted: 27 August 2013 / Published online: 9 November 2013 # Springer Science+Business Media Dordrecht 2013 Abstract Most scientific assessments for climate change adaptation and risk reduction are based on scenarios for climatic change. Scenarios for socio-economic development, particularly in terms of vulnerability and adaptive capacity, are largely lacking. This paper focuses on the utility of socio-economic scenarios for vulnerability, risk and adaptation research. The paper introduces the goals and functions of scenarios in general and reflects on the current global debate around shared socio-economic pathways (SSPs). It examines the options and constraints of scenario methods for risk and vulnerability assessments in the context of climate change and natural hazards. Two case studies are used to contrast the opportunities and current constraints in scenario methods at different scales: the global WorldRiskIndex, based on quantitative data and indicators; and a local participatory scenario development process in Jakarta, showing a qualitative approach. The juxtaposition of a quantitative This article is part of a Special Issue on “Advancing Climate Change Adaptation and Risk Management” edited by Joern Birkmann and Reinhard Mechler. Electronic supplementary material The online version of this article (doi:10.1007/s10584-013-0913-2) contains supplementary material, which is available to authorized users. J. Birkmann (*) : T. Welle : M. Garschagen : N. Setiadi Institute for Environment and Human Security, United Nations University, Bonn, Germany e-mail: birkmann@ehs.unu.edu S. L. Cutter Hazards and Vulnerability Research Institute, University of South Carolina, Columbia, SC, USA D. S. Rothman : B. Hughes Pardee Center for International Futures, University of Denver, Denver, USA B. van Ruijven : B. O’Neill National Center for Atmospheric Research (NCAR), Boulder, USA B. L. Preston Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, USA 54 Climatic Change (2015) 133:53–68 approach with global data and a qualitative-participatory local approach provides new insights on how different methods and scenario techniques can be applied in vulnerability and risk research. 1 Introduction The Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) underscores the need for improved consideration of the dynamic nature of vulnerability and its changes over time and in space. The report emphasises that developing estimates about future vulnerability and response capacities is at least as challenging as estimating the likelihood of physical events and so-called extreme events (IPCC 2012, p. 46). The report also expresses the need for improved methods to predict and estimate future vulnerability, but provides few examples on how to conduct such assessments. It becomes critically important to explore whether and how scenario methods (e.g. quantitative and qualitative) can be used in vulnerability research, especially since risk reduction and adaptation needs are dependent on both future climatic conditions as well as future societal conditions. This paper examines the application of scenario methods in vulnerability research. It addresses the following key questions: & & How can scenario methods be applied to vulnerability assessments at different scales to improve the capacity to estimate potential future vulnerability patterns? What are the specific opportunities and constraints of quantitative and more qualitative scenario methods for vulnerability and risk assessments? The key contribution of this paper is to test the applicability of two different scenario methods (top-down and bottom-up) for vulnerability and risk research. The first method is a quantitative vulnerability and risk-assessment approach based on the global WorldRiskIndex concept. The second is a qualitative local-scenario approach (bottom-up) based on a local participatory process developed for Jakarta by a team of risk and adaptation researchers, integrated assessment modellers and urban development experts. The paper bridges the disaster risk and climate change communities. Scenario methods have not been used much in disaster risk research. The climate change community, on the other hand, S. Kienberger Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg, Salzburg, Austria e-mail: stefan.kienberger@sbg.ac.at O. D. Cardona Universidad Nacional de Colombia, Instituto de Estudios Ambientales (IDEA), Campus Palongrande, Manizales, Colombia T. Siagian Statistics Indonesia (BPS), Government of Indonesia, Jakarta, Indonesia D. Hidayati Indonesian Institute of Sciences (LIPI), Jakarta, Indonesia C. R. Binder Department for Geography, University of Munich (LMU), Munich, Germany R. Pulwarty Earth System Research Laboratory, National Oceanic & Atmospheric Administration, Boulder, USA Climatic Change (2015) 133:53–68 55 is heavily engaged in scenario work, especially on aspects related to mitigation (e.g. Special Report on Emission Scenarios [SRES] scenarios) or on the assessment of impacts (see e.g. IPCC 1994). For example, scenarios have been used to examine the influence of development and climate change on the incidence of future infectious disease mortality (Tol et al. 2007). Using proxy indicators (infant mortality, for example where data are more readily available) to project future disease mortality, the scenarios suggest that changes in development indicators (poverty, literacy) influence infant mortality rates, which in turn lead to proportional changes in the potential malaria death toll, because the two are closely related. However, broader concepts of human vulnerability and risk are rarely included in such scenarios. The paper begins with an introduction into scenario methods. This is followed by the introduction of a new scenario framework for integrated adaptation and mitigation research and the presentation of the two case studies. The final section presents key conclusions and an outlook for the utilisation of scenarios for assessing future vulnerability patterns. 2 Functions and goals of scenarios Various methods have been developed to create scenarios ranging from simplistic to complex models, qualitative to quantitative methodologies, as well as expert versus nonexpert oriented approaches (Glenn et al. 2009; Gordon 2009). In the area of climate change adaptation and disaster risk reduction, most scenarios have been developed in the domain of natural hazards or physical changes to the climate system (climate change scenarios, emissions scenarios [see SRES] etc.), with less work done on scenarios for vulnerability (e.g. IPCC 1994; Giannini et al. 2011; Jones and Preston 2011). A scenario characterises a hypothetical state of a system in the future (Scholz and Tietje 2002). Scenarios represent a mechanism for describing future trends and/or conditions for a specific point in time, despite the unknown degree of irreducible uncertainty about the future (Kok et al. 2011). Scenarios allow us to illustrate and discuss potential directions and evolutionary paths that development processes might take, drawing attention to the potential consequences for decision-making and management strategies (Glenn et al. 2009; van Vuuren et al. 2012a). Generally speaking, scenarios: & & & & make the future(s) more realistic and understandable for decision makers and force new thinking; help understand the significance of uncertainties; illustrate different potential development pathways, underscoring possible and undesirable or desirable development directions; help to identify policies and measures that are appropriate and beneficial in specific scenarios and, hopefully, across a range of possible scenarios (Glenn et al. 2009; Preston et al. 2009; Hallegatte et al. 2011; van Vuuren et al. 2012a, b). Scenarios often fulfil at least two key functions. First, they have analytic and explorative functions in that they facilitate a systematic discussion of current conditions and potential future development trends. Second, scenario development also has a normative function in that it allows for a discussion of desirable or undesirable development patterns and futures. Different scenarios can be compared and more desirable and non-desirable futures can be discussed. Participatory scenario methods also can help identify underlying normative assumptions about development trends and their role within specific framings, e.g. the context of climate change adaptation. Scenario development in participatory or transdisciplinary processes can strengthen trust-building and mutual learning (Wiek et al. 2006). In 56 Climatic Change (2015) 133:53–68 this regard assessments and scenario approaches can be differentiated according to two primary perspectives: top-down versus bottom-up (see Jones and Preston 2011). Today there is a variety of approaches to constructing scenarios. However, most are based on the following criteria: a) they should be plausible, describing a rational route from “here” to “there” that makes causal processes and decisions explicit; b) they should be internally consistent; and c) they should be sufficiently interesting and exciting to make the future “real” enough to elicit strategic responses (see Glenn et al. 2009; Gordon 2009; Hallegatte et al. 2011). 3 The new scenario framework for adaptation and mitigation The climate change research community is presently engaged in the development of a new framework for creating and using scenarios to improve the assessment of climate change, its impacts, and response options (Moss et al. 2010), called the Shared Socio-economic development Pathways (SSPs) (Kriegler et al. 2012; van Vuuren et al. 2012b; O’Neill et al. 2013). One of the key aims of the SSP architecture is to facilitate research and assessment modelling that can inform policymakers about the challenges in mitigation efforts as well as provide information about potential ranges of adaptation efforts. Compared to the former SRES scenarios, the SSPs address the challenges for adaptation. In so doing they provide a stronger link to vulnerability, adaptation, and societal risk to climate change and climate variability (see also van van Ruijven et al. 2013). The SSPs consist of three elements: 1) a narrative (van Vuuren et al. 2013); 2) a set of traditional drivers for Integrated Assessment Models (GDP, population, urbanisation); and 3) several indicators that are relevant for research on impacts, adaptation and vulnerability, such as poverty and governance (van Ruijven et al. 2013). The narratives of the five SSPs explore the different potential combinations of challenges to climate change adaptation and mitigation. These narratives range in the extremes from a sustainable world, with low challenges to both mitigation and adaptation, to a fragmented world with high challenges to both. Narratives in between describe a conventional development world and pathways in which either adaptation or mitigation challenges dominate (see O’Neill et al. 2013). The different criteria used and the underlying assumptions in the SSPs and global modelling approaches need to be evaluated against key information required for vulnerability and risk assessments for both hazards and climate change applications. To begin, it is beneficial to examine how the vulnerability research community could make use of scenarios to underscore that risks due to climate change are not solely dependent on future climatic conditions, but equally dependent on potential changes in societal vulnerability and adaptive capacity (see IPCC 2012, p. 67–90). To illustrate how scenarios can be used to link vulnerability and risk assessment to climate change adaptation, we use two case studies representing a top-down versus bottom-up approach. 4 Scenarios for vulnerability 4.1 Conceptual basis and definitions It is important to note that the terms vulnerability, risk, and mitigation are understood differently in the Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) communities (Schipper 2009; Birkmann and von Teichman 2010). The WorldRiskIndex, for Climatic Change (2015) 133:53–68 57 example, clearly differentiates between natural hazards (e.g. flood, drought, sea level rise) and the vulnerabilities of a society. In this paper we follow the understanding of vulnerability based on the IPCC special report SREX, which defines it as the propensity and predisposition to be adversely affected (IPCC 2012, p. 564). This definition is commensurate with the understanding applied in the DRR community (United Nations/ISDR 2004; IPCC 2012). In climate change research the term sensitivity is often used to further operationalize vulnerability (e.g. see Tol and Yohe 2007), while in disaster risk reduction terms such as susceptibility and fragility are applied. Susceptibility (or fragility) describes the predisposition of elements at risk to suffer harm and is seen as a sub-component of vulnerability. While sensitivity refers to the degree of responsiveness of an exposure unit to climate change, whether beneficial or detrimental (IPCC 1994). In practice criteria and assessments for susceptibility and sensitivity overlap. Finally, vulnerable people and systems have also capacities to respond to hazards in terms of coping or adaptation. Thus we view coping and adaptive capacities as closely linked to vulnerability (see e.g. the WorldRiskIndex). 4.2 Global top-down: the WorldRiskIndex The WorldRiskIndex provides a quantitative test case for exploring how scenario data can be incorporated into risk and vulnerability assessments at a global scale using a top-down approach. It is based on this understanding of vulnerability defined above. It views risk as a product of the interaction of a hazardous event with the vulnerability of a society or, using the conventional risk equation, risk is the probability of an occurrence of a hazardous event multiplied by the consequences. The WorldRiskIndex uses four components in its construction: a) exposure to natural hazards (including frequency and intensity); b) the susceptibility of people and societies exposed; c) their coping capacities; and d) adaptive capacities (Fig. 1). The terms are discussed in detail in the specific sub-sections below (e.g. exposure, susceptibility). The WorldRiskIndex underscores that risks in the light of climate change and natural hazards are not solely dependent on the hazard, but also on the vulnerability of a society including its exposure (see details in the supplement S1). The calculation of exposure includes hazard frequency and yields the number of people exposed to a natural hazard and climate change impacts. The other three components (susceptibility, coping capacity and adaptive capacity) focus on the vulnerability of societies and social actors. The four components include 28 specific indicators (Fig. 1) (Birkmann et al. 2011, and supplements S2, S3). While some indicators of the WorldRiskIndex are found in scenarios for climate change mitigation and adaptation, such as GDP per capita and poverty rates, other indicators that are more specific to the disaster risk context, such as the number of people with hazard insurance, are absent. Previous versions of the WorldRiskIndex have been based on past and present data in order to calculate present national risk and vulnerability levels. To make the methodology amenable for exploring conditions yet to come, it is necessary to calculate future values of indicators for all the vulnerability components. Those future indicators result from three different scenarios provided by the Pardee Center and generated using the International Futures system (IFs).1 IFs is a large-scale integrated database and global modelling system 1 All of the scenario data used is based on the data within the Base Case, Security First and Sustainability First scenarios version 6.68 of IFs. Several of the variables used in this analysis will be available as part of the SSP process. For instance, population, GDP and urbanisation projections on the country level are currently available while other indicators will be produced as output of integrated assessment models (including the IFs) and other approaches. The IFs dataset is currently the most consistently available projection for these indicators. 58 Climatic Change (2015) 133:53–68 Fig. 1 Indicators used within the WorldRiskIndex representing 183 national entities (Hughes et al. 2011, pp. 30–32; see also supplements S7 and S8, and IFs project website http://www.ifs.du.edu). The modelling system contains demographic, economic, health, infrastructure, energy, agricultural, socio-political and environmental sub-systems. It is theory and data driven and starts from historical data and draws upon standard approaches to modelling specific issue areas (Mathers and Loncar 2006) whenever possible. The model provides global results with national scale resolution annually from a base year of 2010 for any horizon through to 2100. In recent years, IFs has been used to explore patterns of potential human progress, addressing income poverty (Hughes et al. 2009), education (Dickson et al. 2010), health (Hughes et al. 2011), infrastructure (Rothman et al. 2013), and domestic governance (Hughes et al. 2013). However, scenario data, particularly for the coping capacity and adaptive capacities components (Fig. 1) are not yet available within Integrated Models that run such scenarios at the global scale. As a result, scenarios were only used to calculate the exposure and susceptibility components of the WorldRiskIndex. Three different scenarios were used for each of the 183 countries for the years 2010 and 2035. The first scenario is the “Base Case” scenario, reflecting a dynamic business as usual path. The second scenario, “Security First”, is characterised by governments and private sectors that focus on improving human well-being primarily for the rich and powerful people in society. The third scenario, “Sustainability First”, assumes successful collaborations between government, civil society and the private sector to improve the environment and the human well-being taking into account equity, transparency and accountability. In-depth descriptions of these scenarios can be found in the supplement (part S8) to this paper and in the GEO-4 report (UNEP 2007). 4.2.1 Exposure of people The IFs model generates population scenarios at the country level, but these do not differentiate between people exposed or not exposed to natural hazards and climate change impacts. Future physical exposure (to floods, cyclones, droughts and sea level rise) is mainly determined by the different scenarios of future population growth based on existing hazard and exposure patterns in 2010 (see Welle et al. 2012 and supplements S2, S5). Increasing average annual exposure related to floods, cyclones, droughts and sea level rise is seen for each continent, with the exception of Europe, where the trend in exposure is Climatic Change (2015) 133:53–68 59 reversed beginning in 2025 (see Fig. 2). This downward trend is due to demographic change (e.g. most notably declining populations). Large increases in the number of people exposed to hazards are shown in absolute and relative terms for Asia and in terms of relative increases in Africa. Recent global studies such as the IPCC SREX report support these general exposure trends and global hotspots, particularly with regard to floods and tropical cyclones in Asia (IPCC 2012, pp. 240–241, Peduzzi et al. 2012). Overall, the findings underscore that exposure scenarios can be developed and these can highlight regions of the world that might experience large increases in population exposure to natural hazards and climate change impacts due to natural population growth and potential migration processes. However, this approach to exposure scenarios has limitations. The most important is the difficulty in calculating specific future hazard patterns. Reliance on projected population growth for hazard zones based on present day may underrepresent the true nature of the hazard zone in the future. 4.2.2 Susceptibility We define susceptibility as conditions of exposed people or societies that make them more likely to experience harm and to be adversely affected by a natural hazard or climate change. Hence, susceptibility is a key characteristic of the propensity to be adversely affected. Changes in susceptibility can be measured in absolute or relative terms. In absolute terms, most countries can be expected to see improvements, i.e. their susceptibility will fall over time. However, the rate at which this occurs will likely differ by country. Past crises and disasters clearly show that societal conditions make a significant difference in terms of harm and loss experienced in such events (IPCC 2012). While the indicators can help to identify countries with a high level of susceptibility, they cannot predict the impact of individual disasters. Relative levels of susceptibility permit comparisons between countries and show shifts that could reflect the rate of change or the nature of exposure. All seven indicators used to measure the susceptibility of societies and people exposed can be calculated using the IFs model (see supplements S1–S6 and Fig. 1). Indicators such as Estimated future physical exposure for three scenarios 78,00 70,20 76,00 70,00 74,00 760,00 69,80 72,00 740,00 69,60 70,00 720,00 69,40 68,00 69,20 700,00 66,00 69,00 68,80 62,00 60,00 2010 68,60 2010 2015 2020 2025 2030 680,00 Europe 64,00 2015 2020 2025 2030 660,00 640,00 2035 2035 620,00 North and Central America Asia 600,00 2010 2015 2020 2025 2030 2035 Africa Estimated future average "Physical Exposure"(to Floods, Cyclone, Droughts per Year and Sea Level Rise of 1 m in 100 years) in millions of people assuming constant hazard pattern for three different scenarios Base case Scenario Security First Scenario Sustainability First Scenario South America 200,0 0 190,0 0 180,0 0 Australia and Oceania 170,0 0 49,00 160,0 0 47,00 150,0 0 45,00 140,0 0 43,00 130,0 0 6,50 6,00 120,0 0 41,00 5,50 110,0 0 39,00 100,0 0 2010 37,00 35,00 2010 2015 2020 2025 2030 2035 5,00 2015 2020 2025 2030 2035 4,50 4,00 2010 2015 2020 2025 2030 2035 Fig. 2 Changes in the exposure of people (in millions) per continent to natural hazards and climate change impacts based on three different scenarios (Base Case (blue line), Security First (red line) and Sustainability First (green line)). Source: own map based on data from PREVIEW and Pardee Center 60 Climatic Change (2015) 133:53–68 for poverty (population living on $1.25 USD per day) or the dependency ratio and the Gini index are key proxies for estimating vulnerability to natural hazards and climate change impacts. High levels of poverty and a large proportion of elderly and young people compared to the population in working age as well as a very unequal distribution of wealth (Gini Index) within a country increase the likelihood that extreme events and hazards have significant negative consequences (see supplement S1). The results shown in Fig. 3 support the key findings of the WorldRiskIndex in 2011 (Birkmann et al. 2011; Welle et al. 2012). The calculations highlight that global hotspots of susceptibility are, at present, located primarily in Africa, South Asia, South-East Asia and Latin America. The scenario data show important dynamics in relative susceptibility at a global scale (Fig. 4). For example, the analysis reveals that the three scenarios differ for Bolivia and Pakistan. Bolivia remains in the medium susceptibility class in the “Base Case” and the “Sustainability First” scenarios, although some indicators such as population without access to sanitation and without access to clean water are quite different in these scenarios. In contrast Bolivia is classified as highly susceptible in 2035 in the “Security First” scenario, due to an increase in the percentage rate of people without access to improved sanitation (43 %) followed by the high percentage of people undernourished (13 %) and a low GDP compared to the values in the other two scenarios. In contrast Pakistan is classified as highly susceptible in the “Base Case” and the “Security First” scenarios in 2035. Under the “Sustainability First” scenario, however, Pakistan improves its conditions and shifts into medium susceptibility, primarily due to a lower percentage of people living in poverty and a reduction of the population undernourished. In addition, the “Sustainability First” scenario reveals a significant reduction of susceptibility for various countries within Africa such as Mali, Niger, Tanzania and Benin compared to the “Security First” and the “Base Case” scenarios (see Fig. 4). If we compare all three scenarios, “Base Case”, “Security First” and “Sustainability First”, using World Bank income groups (World Bank 2013) we see significant differences in the levels of, and changes in, absolute susceptibility between these country groups (see supplement S6). Susceptibility using the Base Case scenario 2010 Base Case 2010 Each country could have a maximum of 100 susceptibility points Classification method: Quantile 8,78 - 15,45 15,46 - 21,89 21,90 - 31,56 31,57 - 48,16 48,17 - 66,60 no data Fig. 3 Present susceptibility and its global distribution using the methodology of the WorldRiskIndex. Source: Own map based on the WorldRiskIndex (see Birkmann et al. 2011 and Welle et al. 2012) and data of the Pardee Center (see Hughes et al. 2011) Climatic Change (2015) 133:53–68 61 Susceptibility scenarios for 2035 Base Case Security First Sustainability First Each country could have a maximum of 100 susceptibility points Classification method: same class limits as LB 2010 8,78 - 15,45 very low 15,46 - 21,89 low 21,90 - 31,56 medium 48,17 - 66,60 very high 31,57 - 48,16 high no data Fig. 4 Scenarios for susceptibility for the year 2035 using the WorldRiskIndex indicators Overall, the application of scenario data to a global risk assessment tool (WorldRiskIndex) is feasible. It shows some interesting differences in terms of future relative susceptibility of countries and between different country income groups. Limits 62 Climatic Change (2015) 133:53–68 and constraints are discussed in the final part of the paper. While global quantitative index and modelling approaches are often developed by experts such as illustrated above by the WorldRiskIndex, local and qualitative scenarios have different functions aiming for the coproduction of knowledge and the integration of stakeholder knowledge and values (Jones and Preston 2011). 4.3 Local bottom-up: Jakarta, Indonesia A local participatory – bottom-up – scenario approach for the city region of Jakarta in Indonesia is used as a contrasting example of scenario approaches. The results are based on a workshop of the 8th meeting of the UNU-EHS Expert Working Group on Measuring Vulnerability in Indonesia in July 2012 involving international, national and local experts (see supplement S9 and website UNU-EHS). The case study illustrates how local approaches using qualitative data are structured and what kind of information they can provide for vulnerability and adaptation assessments. Jakarta is one of Asia’s megacities most exposed to natural hazards, notably flooding. Future exposure and susceptibility patterns depend heavily on the socio-economic development pathways of the city, which are in turn linked to land subsidence, urban sprawl, and social development. Jakarta serves as a prime example for exploring the connections between local urban development pathways and vulnerability trends through scenarios. 4.3.1 Methodology Participatory and qualitative scenario processes often contain three phases: a preparation phase, the scenario development phase, and an evaluation or testing phase (Glenn et al. 2009; Gordon 2009). Participatory scenario planning is not new, and has been applied for example in the context of sustainable development research (Khakee 1999). However, participatory scenario development differs from participatory community risk assessment (van Aalst et al. 2008) in the sense that it goes beyond the analysis and discussion of past and present trends, and incorporates likely future ones. Based on the workshop with international, national and local experts and stakeholders (see supplement S9), a multi-dimensional concept of urban development and adaptation was outlined, mainly focusing on key variables and trends of social, economic, ecological and institutional issues linked to vulnerability, risk and adaptation. The scenario development followed the three phases outlined above and is described in detail in the supplement (see supplement S9). The moderators defined one axis as scenarios of adaptive versus nonadaptive development in the context of climate change. The second axis was defined by local and national experts and practitioners based on current development patterns and future visions. The four-scenario spaces are based on these two axes (see Fig. 5). 4.3.2 Findings The discussion of the indicators and criteria to visualize an increasing or decreasing vulnerability and respective trends, such as poverty, migration, income inequalities, role of Forgein Direct Investement (FDI) (see Fig. 5) was done jointly and respective topics, indicators and criteria were mapped on a white board. This allowed a transparent and understandable scenario discussion. The documentation and visualisation was also helpful in the sense that contrasting alternative scenarios for Jakarta could be checked and critically reviewed by other participants (third phase of scenario construction). Figure 5 shows Climatic Change (2015) 133:53–68 63 Fig. 5 Participatory scenario development—case study Jakarta different trends and core characteristics associated with vulnerability and adaptive capacity. In contrast to the quantitative global approach that resulted in precise numbers and measurable indicators, the participatory scenario method in Indonesia provided contextual information regarding core characteristics and trends of vulnerability - including adaptive capacity - under different scenarios. Since the experts and stakeholders in the excersise had different backgrounds and only limited statistical expertise, the assessment did not aim for developing a specific set of data or measurement guidelines. However, the participatory scenario discussion encompasses indicators and criteria for vulnerability that are now, after the workshop, being examined in terms of data available (see supplement S9.1). The ongoing cooperation with Indonesian scientists shows that respective data can be gathered, however, the type of assessment and the results are quite different from a quantitative approach. That means the core result of this assessment is a vulnerability profile narrative, one with alternative futures. For example, the results reveal (see Fig. 5) that migration, poverty, social security, labour, energy use and governance were key themes identified as shaping the future and hence were used to judge whether the city region will develop into a more adaptive or more mal-adaptive direction. The terms adaptive and mal-adaptive were used as broader categories, yet there was consensus that the criteria and indicators developed are also characteristics of vulnerability (such as poverty, income inequalities etc.). Often, similar issues, but with different trend directions and magnitudes (e.g. in-migration) were discussed regarding the different scenario spaces. The findings underscore that the vision of a high-tech city with non-labour intensive industries is not necessarily an adaptive cityregion where people are less vulnerable. If present trends regarding in-migration and poverty cannot be reversed, a high-tech city might even lead to higher vulnerability, since the gap 64 Climatic Change (2015) 133:53–68 between high skilled labor demand and in-migrants with low qualifications might be intensified (see Fig. 5, scenario IV). While storlylines or narratives in the SSP process also encompass a description about future vulnerabilities, the locally-derived vulnerability profiles here are often directly linked to experiences in the past and the local knowledge of stakeholders and experts involved. The participatory development of qualitative local scenarios contributes an important option to enhance not only the thematic focus but also the methodological toolkit for exploring future vulnerability and risk. The participatory bottom-up approach offers a venue for different stakeholders to jointly discuss key trends that are likely to shape the future (see more details in the supplement S9). Also normative aspects, such as the question “what is a desirable future?” were discussed during the process. However, the exercise also shows that local participatory scenarios are often limited in terms of capturing temporal dynamics or timelines compared to quantitative top-down scenarios that are based on extrapolated data (see e.g. Fig. 2). The participatory scenarios, however, do show future trends based on local desires and expectations, but these are less exact in their measurement. The development of local scenarios reflects specific place-based knowledge that does not necessarily provide a comprehensive or all-embracing picture. Certainly disagreements and different judgements amongst the experts remain a challenge for assessing the validity of single scenarios and for generating a coherent overall scenario framework. However, in the spirit of focus group discussions, such disputes also proved highly informative and added a rich context to the scenarios. 5 Discussion and conclusions Overall, the juxtaposition of two methodologically different approaches (top-down and bottom-up), using two very different scales, underscores the broad spectrum of applications of scenario techniques in research into vulnerability, risk and adaptation. While global quantitative scenario approaches on exposure and susceptibility allow for exploration of large-scale trends and patterns, the local qualitative and participatory approach enables researchers and practitioners to understand, examine, and discuss the links between global or sub-national trends (e.g. SSPs) and the vulnerability in specific regions or municipalities. The two approaches contain very different epistemologies and methods, however, a key similarity is that both allow for an examination of present and future trends in vulnerability under different scenarios and hence provide a thinking tool about the drivers that shape potential future conditions. Qualitative approaches provide broader contextual details on future patterns of vulnerability and disaster risk to climate change and extreme events (e.g. reduced poverty, high in-migration), while quantitative approaches allow for a more detailed analysis or visualization of trend dynamics within a specified time period (see e.g. Fig. 2). The visualisation of scenarios for population exposure to natural hazards and climate change impacts as well as the scenarios for susceptibility in the year 2035 show that socioeconomic development pathways and demographic change (e.g. in Europe for example) are important factors in determining different levels of susceptibility and exposure in various scenarios. The hypothesis that elderly people are more susceptible to hazards influenced by climate change (e.g. heat stress, floods) compared to people in the working age is, however, based on present knowledge. It is defined through the choice of indicators to estimate vulnerability (see supplement S1). It is very unlikely, but still possible, that technical and medical innovations in the long-term would change this difference in susceptibility between elderly and working-age people. Consequently, uncertainties and Climatic Change (2015) 133:53–68 65 limits of predictability apply to different types of causal-relationships in vulnerability studies and selected indicators. Nonetheless, the anticipation of different trends and development pathways within various scenarios embedded in risk and vulnerability assessments enhance present approaches and strategies. Various disaster risk reduction strategies are still characterised by a dominant focus on present socio-economic conditions—particularly present vulnerability profiles. In contrast, scenario approaches like the ones presented here (top-down or bottomup) can, in principle, provide a lens to think about future conditions and those factors that will modify vulnerability. Most notably, the analysis of susceptibility in the year 2035 for the three scenarios shows significant changes in Asia (China, Pakistan, etc.), Africa (e.g. Democratic Republic of Congo) and Latin America (e.g. Bolivia). These changes are determined by different factors, but can be examined in more detail for policymaking. The different scenario results for China or Pakistan, for example, underscore that socio-economic conditions and shifts in properties such as demographic structures or poverty levels at the national scale are significant drivers of vulnerability and might also heavily influence sub-national and local vulnerability conditions. However, the precise interpretation of the different country results is still a challenge and uncertainty remains, for example with regard to whether these countries are more likely to develop in the direction of the base case, the security first or the sustainability first scenarios. In addition, the driving forces of vulnerability might change over time meaning that some additional factors that are not yet sufficiently identified can have an important effect on vulnerability in 2035. Consequently, the timeframe of the scenarios and the different assumptions have to be considered when they are applied in policymaking. However, scenarios can help shaping future-oriented policies for disaster risk management and climate change adaptation by anticipating likely conditions in terms of exposure or susceptibility at some distant time. An added value of the overall approach is that the model results and scenario expertise of the Integrated Assessment Modelling (IAM) community is used within tools for vulnerability and risk assessment. But comprehensive data sets for assessing future scenarios for coping and adaptation is still lacking. Therefore, an important constraint to present scenario construction is the limited data for modelling coping and adaptation as shown in the example of the WorldRiskIndex. Compared to the global quantitative scenarios, local participatory scenarios capture coping and adaptation challenges through qualitative data based on the experiences and knowledge of stakeholders involved. As shown in the Jakarta example, participatory, local approaches can be thematically much broader and place-specific; however the trends and criteria used also depend heavily on the composition of the participants and experts in such scenario exercises. In contrast to quantitative approaches, these qualitative scenarios (see Fig. 5) often do not capture temporal dynamics, a clear constraint in their application for policy making. In general, bottom-up approaches provide a process for discussing different potential futures linked to the experiences and expertise of the stakeholders involved. There is great potential for linking global and local scenarios. Scenarios at the local level need to be informed by potential global trends and development patterns, such as regional economic growth or population growth. In contrast, local scenario approaches check the relevance of the topics and indicators used at the global level to describe susceptibility and exposure. In addition, they might also raise awareness about new and locally specific issues that need to be addressed when thinking about future development trends in vulnerability, risk and adaptation at the local level, such as issues of migration and the performance of natural hazard management (see Fig. 5). However, as shown in the test cases, the linking of 66 Climatic Change (2015) 133:53–68 different scenario methods (qualitative versus quantitative) and bridging the different scales is challenging. Some relevant trends and indicators at the local scale cannot be applied for the identification of different levels of vulnerability and risk at the global scale and vice versa. The case studies provide valuable lessons with respect to future development and application of the Shared Socio-economic Pathways (SSPs). To maximise their utility to diverse research communities and disciplines, the SSPs should remain sufficiently flexible to inform both top-down global scale scenario, development-based quantitative indicators as well as bottom-up, participatory scenarios that are more qualitative in nature. The development of quantitative, national-scale indicators by the IAM community as part of the SSP process creates opportunities for expanding tools such as the WorldRiskIndex to accommodate a greater array of alternative development pathways. However, the Jakarta case study illustrates that local aspects of societal development and normative considerations of actors are equally important in developing legitimate scenarios. 6 Future research Future research needs to focus on improving the links between different scenarios and assessments at different scales as well as the improvement of data for capturing societal response capacities to hazards and climate change. More precisely, research has to examine the mechanisms for bridging the various scenario approaches across different spatial and temporal scales as well as in terms of different methods used (qualitative versus quantitative, top-down versus bottom-up). In addition, it is essential to improve the data bases for capturing coping and adaptation processes that have not sufficiently been captured in existing global models. This paper provides a first step towards a better understanding on how scenarios might enhance present risk and vulnerability assessment tools. 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Climatic Change. doi:10.1007/s10584-013-0906-1 Welle T, Birkmann J, Rhyner J, Witting M, Wolfertz J (2012) WorldRiskIndex 2012: concept and results. In Alliance Development Works (eds.): WorldRiskReport. Berlin, pp. 11–26 Wiek A, Binder CR, Scholz RW (2006) Functions of scenarios in transition processes. Futures 38(7):740–766 World Bank (2013) Global economic and social data of the World Bank; available under: http:// data.worldbank.org/indicator/NY.GNP.PCAP.CD 1 Measuring vulnerability to promote disaster-resilient societies: Conceptual frameworks and definitions Jörn Birkmann Introduction This chapter stresses the need for a paradigm shift from quantification and analysis of the hazard to the identification, assessment and ranking of vulnerabilities. It underlines the importance of measuring vulnerability and developing indicators to reduce risk and the vulnerability of societies at risk, as mentioned in the final document of the 2005 World Conference on Disaster Reduction. Different conceptual frameworks of vulnerability in the context of disaster resilience are presented. The links between vulnerability and sustainable development are also discussed. From hazard analysis to assessment of vulnerability The ability to measure vulnerability is increasingly being seen as a key step towards effective risk reduction and the promotion of a culture of disaster resilience. In the light of increasing frequency of disasters and continuing environmental degradation, measuring vulnerability is a crucial task if science is to help support the transition to a more sustainable world (Kasperson et al., 2005). UN Secretary-General Kofi Annan has underlined the fact that hazards only become disasters when people’s lives and livelihoods are swept away (Annan, 2003). His view is in contrast to research and strategies in the past, which were often purely hazard-oriented (Lewis, 1999). 9 (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 9) 10 JÖRN BIRKMANN Instead of defining disasters primarily as physical occurrences, requiring largely technological solutions, disasters are better viewed as a result of the complex interaction between a potentially damaging physical event (e.g. floods, droughts, fire, earthquakes and storms) and the vulnerability of a society, its infrastructure, economy and environment, which are determined by human behaviour. Viewed in this light, natural disasters can and should be understood as ‘‘un-natural disasters’’ (Cardona, 1993; van Ginkel, 2005). Thus the promotion of disaster-resilient societies requires a paradigm shift away from the primary focus on natural hazards and their quantification towards the identification, assessment and ranking of various vulnerabilities (Maskrey, 1993; Lavell, 1996; Bogardi and Birkmann, 2004). It is part of UNU-EHS’s mission to contribute to the identification of various vulnerabilities and the development and testing of relevant indicators and assessment tools (Birkmann, 2005) in order to expand the environmental dimension of human security further (Brauch, 2005). In the final document of the World Conference on Disaster Reduction, ‘‘Hyogo Framework for Action 2005–2015’’, the international community underlined the need to promote strategic and systematic approaches to reducing vulnerabilities and risks to hazards (United Nations (UN), 2005, preamble). The declaration points out that: The starting point for reducing disaster risk and for promoting a culture of disaster resilience lies in the knowledge of the hazards and the physical, social, economic and environmental vulnerabilities to disasters that most societies face, and of the ways in which hazards and vulnerabilities are changing in the short and long term, followed by action taken on the basis of that knowledge. (UN, 2005) In this context the Hyogo Framework stresses the need to develop indicators of vulnerability as a ‘‘key activity’’: Develop systems of indicators of disaster risk and vulnerability at national and sub-national scales that will enable decision-makers to assess the impact of disasters on social, economic and environmental conditions and disseminate the results to decision makers, the public and populations at risk. (UN, 2005) Although the international community does not formulate guidelines on how to develop indicators or indicator systems to assess vulnerability, the Hyogo Framework for Action underlines the fact that impacts of disasters on (1) social, (2) economic, and (3) environmental conditions should be examined through such indicators. Since sustainable development is characterised by three pillars – social, economic and environmental (UN, 1993; WCED, 1987) – the formulation used in the Hyogo Framework for (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 10) MEASURING VULNERABILITY 11 Action can be interpreted as implying a link between vulnerability assessment and sustainable development. Moreover, the declaration underlines the necessity to develop methods and indicators which, based on those recommendations, can be used in policy and decision-making processes. Furthermore, it is evident that measuring vulnerability requires, first and foremost, a clear understanding and definition of the concept of vulnerability. Definitions The current literature encompasses more than 25 different definitions, concepts and methods to systematise vulnerability (for example, Chambers, 1989; Bohle 2001, Wisner et al., 2004; Downing et al., 2006; UN/ ISDR, 2004: 16; Pelling, 2003: 5; Luers, 2005: 215; Green, 2004: 323; UN-Habitat, 2003: 151; Schneiderbauer and Ehrlich, 2004; van Dillen, 2004: 9.; Turner et al., 2003: 8074; Cardona, 2004b: 37). The website of the ProVention Consortium includes about 20 manuals and different guidebooks on how to estimate vulnerability and risk (ProVention Consortium website). These manuals also include different definitions and various conceptual frameworks of vulnerability. Although vulnerability has to be viewed in its multifaceted nature (Bohle, 2002a, 2002b), the different definitions and approaches show it is not clear just what ‘‘vulnerability’’ stands for as a scientific concept (Bogardi and Birkmann, 2004: 76). We are still dealing with a paradox: we aim to measure vulnerability, yet we cannot define it precisely. Although there is no universal definition of vulnerability, various disciplines have developed their own definitions and pre-analytic visions of what vulnerability means. An overview of different definitions is given by Thywissen in this book, and can also be studied for example in Schneiderbauer and Ehrlich (2004), Green (2004) and Cardona et al. (2003). Nevertheless, it is useful to give a brief introduction of the terms vulnerability, hazard, risk and coping capacity in order to discuss different concepts of how to systematise vulnerability. Vulnerability Vulnerability is a concept that evolved out of the social sciences and was introduced as a response to the purely hazard-oriented perception of disaster risk in the 1970s (Schneiderbauer and Ehrlich, 2004: 13). Since the 1980s, the dominance of hazard-oriented prediction strategies based on technical interventions has been increasingly challenged by the alternative paradigm of using vulnerability as the starting point for risk reduc- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 11) 12 JÖRN BIRKMANN tion. This approach combines the susceptibility of people and communities exposed with their social, economic and cultural abilities to cope with the damage that could occur (Hilhorst and Bankoff, 2004: 2). Additionally, some authors distinguish between social vulnerability on the one hand, which deals with the susceptibility of humans and the conditions necessary for their survival and adaptation, and biophysical vulnerability on the other (WBGU, 2005: 33). Biophysical vulnerability in this context is a concept developed from global environmental change research, where it is widely used to describe the extent to which a system is vulnerable to adverse effects of climate change and to what extent it is (un-)able to adapt to such impacts (see in detail WBGU, 2005: 33). Although there is still much uncertainty about what the term vulnerability covers, Cardona (2004b) underlines the fact that the concept of vulnerability helped to clarify the concepts of risk and disaster. He views vulnerability as an intrinsic predisposition to be affected by or to be susceptible to damage; that means vulnerability represents the system or the community’s physical, economic, social or political susceptibility to damage as the result of a hazardous event of natural or anthropogenic origin (Cardona, 2004: 37– 51). One of the best-known definitions was formulated by the International Strategy for Disaster Reduction (UN/ISDR), which defines vulnerability as: The conditions determined by physical, social, economic and environmental factors or processes, which increase the susceptibility of a community to the impact of hazards. (UN/ISDR, 2004) In contrast, the United National Development Programme (UNDP) defines vulnerability as: a human condition or process resulting from physical, social, economic and environmental factors, which determine the likelihood and scale of damage from the impact of a given hazard. (UNDP, 2004: 11) While the definition of vulnerability used by the ISDR encompasses various conditions that have an impact on the susceptibility of a community, the UNDP definition understands vulnerability as a human condition or process. The human-centred definition used by UNDP affects the method used to calculate its Disaster Risk Index, especially with regard to the calculation of relative vulnerability (UNDP, 2004: 32). The Disaster Risk Index measures the relative vulnerability of a country to a given hazard by dividing the number of people killed by the number of people exposed (see Peduzzi, Chapter 8; Pelling, Chapter 7). Using people killed (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 12) MEASURING VULNERABILITY 13 divided by people exposed as the indicator to measure relative vulnerability corresponds with the understanding that vulnerability is primarily a human condition. Furthermore, the lack of appropriate data at the global level has restricted UNDP’s opportunities to establish a broader index. Although one has to take into account that human society is the main focus of concepts of vulnerability, a fundamental question has to be clarified: can human vulnerability be adequately characterised without considering simultaneously the vulnerability of the ‘‘surrounding’’ ecosphere? (e.g. Turner et al., 2003). Furthermore, other authors, such as Vogel and O’Brien (2004: 4) stress the fact that vulnerability is: " multi-dimensional and differential (varies across physical space and among and within social groups) " scale dependent (with regard to time, space and units of analysis such as individual, household, region, system) " dynamic (the characteristics and driving forces of vulnerability change over time). Regarding the concept of social vulnerability, Cannon et al. (2003: 5) argue that social vulnerability is much more than the likelihood of buildings collapsing and infrastructure being damaged. They describe social vulnerability as a set of characteristics that includes a person’s: " initial well-being (nutritional status, physical and mental health) " livelihood and resilience (assets and capitals, income and qualifications) " self-protection (capability and willingness to build a safe home, use a safe site) " social protection (preparedness and mitigation measures) " social and political networks and institutions (social capital, institutional environment and the like). The definition by Cannon et al. (2003) reflects the fact that vulnerability is only partially determined by the type of hazard; it is mainly driven by precarious livelihoods, the degree of self-protection or social protection, qualifications and institutional settings that define the overall context in which a person or a community experiences and responds to the negative impact of a hazardous event (Cannon et al., 2003: 5). However, the concept of social vulnerability also lacks a common definition, which means that different authors use it differently. Current literature reveals the fact that social vulnerability can encompass various aspects and features, which are linked to socially created vulnerabilities. Therefore, the concept of social vulnerability is not limited to social fragilities, but rather includes topics such as social inequalities regarding income, age or gender, as well as characteristics of communities and the built environment, such as the level of urbanisation, growth rates and economic vitality (Cutter et al., 2003: 243). Downing et al. (2006) define six attributes to characterise (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 13) 14 JÖRN BIRKMANN social vulnerability based on the experiences of over two decades of research on this topic. They emphasise that social vulnerability is: " the differential exposure to stresses experienced or anticipated by the different units exposed " a dynamic process " rooted in the actions and multiple attributes of human actors " often determined by social networks in social, economic, political and environmental interactions " manifested simultaneously on more than one scale " influenced and driven by multiple stresses. Consequently, the concept of social vulnerability refers to more than socio-economic impacts, since it can also encompass features of potential physical damage in the built environment (Cutter et al., 2003: 243). Other experts such as Carreño et al. (2005a and 2005b) clearly distinguish between socio-economic fragilities and lack of resilience as social context conditions (that favour the second order impacts) on the one hand, and the physical damage caused by exposure and physical susceptibility of the built environment on the other hand (related to first-order impacts) (Cardona, 1999 and 2001; Cardona and Hurtado, 2000a, 2000b, 2000c; Cardona and Barbat, 2000; Carreño et al., 2004, 2005a, 2005b). Downing et al. (2006) underline the fact that the concept of social vulnerability encompasses various vulnerability features, which are driven by multiple stresses and differential exposure, and are often rooted in multiple attributes of human actors and social networks. One has to conclude that the concept of social vulnerability is much more broadly used than just for the estimation of traditional social aspects of vulnerability (gender, age and income distribution). Seen from the perspective of the social vulnerability school of thinking, ‘‘social vulnerability’’ can also encompass economic and physical aspects, provided they are the expressions of a socially constructed vulnerability. Although the conceptual classification of vulnerability differs, for example between Cutter et al. (2003) and Carreño et al. (2005a and 2005b), both schools of thinking underline the fact that vulnerability should not be limited to an estimation of the direct impacts of a hazardous event. Rather, it has to be seen as the estimation of the wider environment and social circumstances, thus enabling people and communities to cope with the impact of hazardous events or, conversely, limiting their ability to resist the negative impact of the hazardous event. This underlines the fact that vulnerability can also take into account the coping capacity and resilience of the potentially affected society. However, it important to acknowledge that also the analysis of damage patterns can contribute to the identification of revealed vulnerabilities as well as to the estimation of current and potential vulnerabilities in the future. Therefore, the challenge lies in devel- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 14) MEASURING VULNERABILITY 15 oping a balanced approach between the general context and the macro indicators, on one side, and more precise and specific indicators on the other, which can also be based on revealed vulnerabilities in the past. Coping capacity According to ISDR, coping capacity can be defined as: a combination of all strengths and resources available within a community or organization that can reduce the level of risk, or the effects of a disaster. (UN/ISDR, 2002) Vulnerability and coping capacity manifest themselves once a vulnerable community is exposed to a hazardous event. In this context hazard is understood as: A potentially damaging physical event, phenomenon and/or human activity, which may cause the loss of life or injury, property damage, social and economic disruption or environmental degradation. (UN/ISDR, 2002) Compared to the terms hazard and vulnerability, the term risk can be described as the product of the interaction between hazard and vulnerability. In risk sciences the term risk encompasses the probability and the amount of harmful consequences or expected losses resulting from interactions between natural or human induced hazards and vulnerable conditions. (UN/ISDR, 2002) Moreover, the term resilience gained high recognition in the Hyogo Framework and the debate thereafter. The current literature reveals different interpretations of the term, especially concerning the question of whether resilience is defined as the capacity to absorb disturbances or shocks, and is thus more linked to the understanding of resistance, or whether the term refers to the regenerative abilities of a social or an ecosystem, encompassing the ability to learn and adapt to incremental changes and sudden shocks while maintaining its major functions. This meaning relates more to the coping and adaptation phase (see e.g. Adger et al., 2005: 1036; Allenby and Fink, 2005: 1034). In some cases resilience is also understood as the opposite of vulnerability (Adger et al., 2005), while others view vulnerability as the opposite and lack of human security (Bogardi and Brauch, 2005). Generally, a common ground can be seen in the understanding that resilience describes the capability of a system to maintain its basic functions and structures in a time of shocks and (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 15) 16 JÖRN BIRKMANN perturbations and can continue to deliver resources and ecosystem services that are essential for human livelihoods (Adger et al., 2005; Allenby and Fink, 2005). This definition of resilience also implies that the respective system or unit is able to adapt and learn, meaning that the system – e.g. social system, ecosystem or coupled human–environmental system – can mobilise sufficient self-organisation to maintain essential structures and processes within a coping or adaptation process. What have we learned so far? Preliminary observations The overview of key-terms associated with vulnerability and risk has revealed that although the concept of vulnerability has achieved a high degree of recognition in different fields, such as disaster management, environmental change research and development studies, the concept is still somewhat fuzzy and often used with differing connotations. In this context it might be misleading to try to establish a universal definition. Therefore the author provides an overview of the different spheres of the concept of vulnerability (Figure 1.1), without intending to be comprehensive. Nearly all concepts of vulnerability view it as an ‘‘internal side of risk’’, closely linked with the discussion of vulnerability as an intrinsic characteristic of a system or element at risk. That means the conditions of the exposed element or community (susceptibility) at risk are seen as core characteristics of vulnerability (UN/ISDR, 2004; Cardona, 2004a/b: 37; Wisner, 2002: 12/7; Thywissen, in this book) and this can be defined as a common ground (the inner circle in Figure 1.1). Interestingly, the understanding that vulnerability is seen as an internal side of risk and as an intrinsic characteristic of an element at risk can be applied for very different elements, such as communities and social groups (socio-economic conditions, institutional framework), structures and physical characteristics of buildings and lifelines (physical structure), as well as eco-systems and environmental functions and services (ecosystem, environmental capital). An extension of this definition can be seen in definitions such as Wisner’s (2002), which defines vulnerability as the likelihood of injury, death, loss and disruption of livelihood in an extreme event, and/or unusual difficulties in recovering from negative impacts of hazardous events – primarily related to people (Wisner, 2002: 12/7). This definition underlines the fact that the main elements of vulnerability are those conditions that increase and determine the likelihood of injury, death, loss and disruption of livelihood of human beings. Thus a second sphere can be associated with this human-centred definition of the likelihood of death, injury and loss (Figure 1.1). (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 16) MEASURING VULNERABILITY 17 Figure 1.1 Key spheres of the concept of vulnerability. Source: Birkmann 2005. Furthermore, the ‘‘likelihood of injury’’ is extended by the focus of a dualistic structure of vulnerability, which can be observed in the definitions by Wisner (2002) and also partially by Chambers (1989) and Bohle (2001). Wisner clearly identifies the ‘‘likelihood of injury’’ and ‘‘unusual difficulties in recovering’’ from such events as the key features of vulnerability. This means the concept of vulnerability is widened by viewing vulnerability as implying a dualistic approach of susceptibility on the one hand and the unusual difficulties in coping and recovering on the other. However, Bohle’s double structure of vulnerability (Figure 1.1) is not just ‘‘exposure’’ and ‘‘coping’’; rather, it refers to vulnerability features which are external to an exposed element or unit at risk and those factors that are internal. The distinction between these two spheres ‘‘external exposure’’ and ‘‘internal coping’’ emphasises that vulnerability deals on the one hand with features and characteristics linked to capaci- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 17) 18 JÖRN BIRKMANN ties to anticipate and cope with the impact of a hazard, and on the other, with the exposure to risks and shocks (Bohle, 2001). In this context a third sphere can be associated with the ‘‘dualistic structure of vulnerability’’, which underlines the fact that vulnerability is shaped and determined by the likelihood of injury (susceptibility, negative definition) and by the ability and capacity to cope with (positive definition) and recover from these stresses and negative impacts of the hazardous event (Wisner, 2002: 12–17). An additional extension of the concept of vulnerability can be seen in the shift from a double structure to a multi-structure. The conceptual framework of Bohle (2001) already stresses the fact that vulnerability is a multifaceted concept, and also the discourse of vulnerability within the climate change and sustainability community (Turner et al., 2003) highlights that vulnerability not only captures susceptibility and coping capacity, but also adaptive capacity, exposure and the interaction with perturbations and stresses. This implies a fourth sphere (Figure 1.1) widening the concept of vulnerability to a multi-structure that encompasses exposure, sensitivity, susceptibility, coping capacity, adaptation and response. While the traditional engineering perspective of vulnerability focused primarily on physical aspects, the current debate regarding vulnerability clearly underlines the necessity to take into account various themes and parameters that shape and drive vulnerability (UN/ISDR, 2004), such as physical, economic, social, environmental and institutional characteristics. Some approaches also stress the necessity to integrate additional global drivers that have an impact on vulnerability, such as globalisation and climate change (Vogel and O’Brien 2004: 3; O’Brien and Leichenko, 2000). This implies that the focus of attention has shifted from a primarily physical structure analysis to a broad interdisciplinary analysis of the multidimensional concept of vulnerability (e.g. Cardona, 2004b: 39–49). The widening of the concept of vulnerability is illustrated in Figure 1.1. It shows that starting from a general basic understanding (first inner sphere), a process of broadening took place and this is shown through the arrow in the figure. The different spheres of the concept of vulnerability are also reflected in the various conceptual frameworks to systematise vulnerability. Selected conceptual frameworks will be discussed in the following pages. Conceptual frameworks of vulnerability The different views on vulnerability are reflected in various analytical concepts and models of how to systematise it. Since these conceptual models are an essential step towards the development of methods mea- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 18) MEASURING VULNERABILITY 19 suring vulnerability and the systematic identification of relevant indicators (Downing, 2004: 19), the following paragraphs give an insight into different conceptual frameworks, such as the double structure of vulnerability as defined by Bohle, selected approaches of the disaster risk community, such as the UN/ISDR framework for disaster risk reduction, and lastly the two conceptual frameworks developed by UNU-EHS. The double structure of vulnerability According to Bohle (2001), vulnerability can be seen as having an external and an internal side. The internal side, coping, relates to the capacity to anticipate, cope with, resist and recover from the impact of a hazard; in contrast, the external side involves exposure to risks and shocks. In social sciences the distinction between the exposure to external threats and the ability to cope with them is often used to underline the double structure of vulnerability (van Dillen, 2004). Based on the perspective of social geography and the intensive famine research carried out by Bohle (2001: 119), the pre-analytic vision of the double structure underlines the fact that vulnerability is the result of interaction between exposure to external stressors and the coping capacity of the affected household, group or society. Thus the definition clearly identifies vulnerability as a potentially detrimental social response to external events and changes such as environmental change. Interestingly, Bohle’s conceptual framework describes exposure to hazards and shocks as a key component of vulnerability itself. Viewed in this way, the term exposure goes beyond mere spatial exposure since it also encompasses features related to the entitlement theory and human ecology perspective. Within the debate of social vulnerability the term exposure also deals with social and institutional features, meaning processes that increase defencelessness and lead to greater danger, such as exclusion from social networks. These alter the exposure of a person or a household to risk (Cannon et al., 2003). Moreover, the conceptual framework of the double structure indicates that vulnerability cannot adequately be characterised without simultaneously considering coping and response capacity, defined here as the internal side of vulnerability. The sustainable livelihood framework The ‘sustainable livelihood framework’ can also be seen as a framework or vade-mecum for vulnerability assessment. Key elements of this approach are the five livelihood assets or capitals (human, natural, financial, social and physical capital), the ‘vulnerability context’ viewed as shocks, trends and seasonality, and the influence of transforming struc- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 19) 20 JÖRN BIRKMANN Figure 1.2 Bohle’s conceptual framework for vulnerability analysis. Source: Bohle, 2001. tures for the livelihood strategies and their outcomes (see in detail DIFID (1999) and Figure 1.3). The sustainable livelihood framework encompasses two major terms, sustainability and livelihoods. The original concept developed by Chambers and Conway (1992) viewed livelihoods as the means of gaining a living, encompassing livelihood capabilities, and tangible and intangible assets. Within the livelihood framework, the term sustainability is often linked to the ability to cope with and recover from stresses and shocks as well as to maintain the natural resource base (DFID, 1999; Chambers and Conway, 1992). The framework emphasises that especially the transforming structures in the governmental system or private sector and respective processes (laws, culture) influence the vulnerability context, and determine both the access to and major influences on livelihood assets of people. The approach underlines the necessity of empowering local marginalised groups in order to reduce vulnerability effectively (see in detail DFID, 1999; Schmidt, 2005). A central objective of the approach was to provide a method that views people and communities on the basis of their daily needs, instead of implementing ready-made, general interven- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 20) MEASURING VULNERABILITY 21 Figure 1.3 The sustainable livelihood framework. Source: DFID, 1999. tions and solutions, without acknowledging the various capabilities poor people offer (de Haan and Zoomers, 2005). The approach views vulnerability as a broad concept, encompassing livelihood assets and their access, and vulnerable context elements such as shocks, seasonality and trends, as well as institutional structures and processes. Although the sustainable livelihood approach underlines the multiple interactions that determine the ability of a person, social group or household to cope with and recover from stresses and shocks, it remains abstract. The transforming structures and processes in particular, including influences and access aspects, remain very general. In this context, de Haan and Zoomers (2005: 33 and 45) emphasise that access and the role of transforming structures are key issues which have not been sufficiently examined so far. In particular, the flexibility of the interchanges of different capitals and assets (human capital, financial capital, social capital) has to be more closely considered, which means that the configuration of power around these assets and capitals as well as the power and processes of transforming structures need to be explored in more depth. They argue that access as a key element in the sustainable livelihood framework heavily depends on the performance of social relations, and therefore more emphasis in sustainable livelihood research should be given to the role of power relations. De Haan and Zoomers conclude that the current concept has the tendency to focus on relatively static (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 21) 22 JÖRN BIRKMANN capitals and activities within different livelihoods and livelihood strategies (de Haan and Zoomers, 2005). Furthermore, it is interesting to note that the concept of livelihoods accounts solely for positive outcomes (livelihood outcomes). Additionally, some of the feedback processes underestimate the role of livelihood outcomes on the environmental sphere; for example, a ‘‘more sustainable use of natural resources’’ can be seen as an important tool to reduce the magnitude and frequency of some natural hazards such as droughts, floods or landslides. These linkages between the human–environmental system play a major role in the resilience discourse (see e.g. Allenby and Fink, 2005; Folke et al., 2002; Adger et al., 2005). Nevertheless, this approach, especially the five livelihood assets, can also serve as an important source and checklist for other approaches aimed at identifying susceptibility and coping capacity for hazards of natural origin. The framework can also be linked to categories used in the disaster risk community such as hazard, exposed and susceptible elements, driving forces/ root causes, and potential outcomes and responses. While the various shocks encompass hazard components, the five livelihood assets could represent elements that are exposed and susceptible, while the transforming structures and processes in other frameworks are viewed as root causes, dynamic pressures or driving forces (see e.g. PAR framework). The livelihood strategies and outcomes can be viewed as a mixture of intervention and response elements. However, the understanding of vulnerability in the sustainable livelihood approach is very broad, also encompassing the hazard sphere. Vulnerability within the framework of hazard and risk A second school, the disaster risk community, defines vulnerability as a component within the context of hazard and risk. This school usually views vulnerability, coping capacity and exposure as separate features. To illustrate this school of thinking three approaches will be presented: the definition of risk within the disaster risk framework by Davidson (1997), adopted by Bollin et al. (2003), the triangle of risk of Villagrán de León (2004), which reflects the ‘‘risk triangle’’ developed by Crichton (1999), and the UN/ISDR framework for disaster risk reduction (2004). Davidson’s (1997) conceptual framework, adopted by Bollin et al. (2003), is shown in Figure 1.4. It views vulnerability as one component of disaster risk. The conceptual framework distinguishes four categories of disaster risk: hazard, exposure, vulnerability and capacity measures (Figure 1.4). This conceptual framework views risk as the sum of hazard, exposure, vulnerability and capacity measures. While hazard is defined through its (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 22) MEASURING VULNERABILITY 23 Figure 1.4 The conceptual framework to identify disaster risk. Source: Davidson, 1997: 5; Bollin et al., 2003: 67. probability and severity, exposure is characterised by structures, population and economy. In contrast, vulnerability has a physical, social, economic and environmental dimension. Capacity and measures – which seem to be closely related to the subject of coping capacity – encompass physical planning, social capacity, economic capacity and management. In contrast to the framework of the double structure of vulnerability developed by Bohle (2001), this approach defines vulnerability as one component of disaster risk and differentiates between exposure, vulnerability and coping capacity (Davidson 1997; Bollin et al., 2003). Villagrán de León also explains vulnerability in the hazard and risk context. He defines a triangle of risk, which consists of the three components of vulner- Figure 1.5 Risk as a result of vulnerability, hazard and deficiencies in preparedness. Source: Villagrán de León, 2001/2004. (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 23) 24 JÖRN BIRKMANN ability, hazard and deficiencies in preparedness (Villagrán de León, 2004: 10). His figure reflects the ‘‘risk triangle’’ developed earlier by Crichton (1999). However, he defines vulnerability as the pre-existing conditions that make infrastructure, processes, services and productivity more prone to be affected by an external hazard. In contrast to the positive definition of coping capacities, he uses the term ‘‘deficiencies in preparedness’’ to capture the lack of coping capacities of a society or a specific element at risk (Villagrán de León, 2001, 2004). Although the term exposure is not directly mentioned, he views exposure primarily as a component of the hazard (Villagrán de León, Chapter 16). The ISDR framework for disaster risk reduction A different conceptual framework was developed by the UN/ISDR. The UN/ISDR framework views vulnerability as a key factor determining risk. According to UN/ISDR, vulnerability can be classified into social, economic, physical and environmental components (see Figure 1.6). Vulnerability assessment is understood as a tool and a pre-condition for effective risk assessment (UN/ISDR, 2004: 14–15). Although the framework provides an important overview of different phases to be taken into account in disaster risk reduction, such as vulnerability analysis, hazard analysis, risk assessment, early warning and response, the framework does not indicate how reducing vulnerability can also reduce risk. Vulnerability is placed outside the risk response and preparedness framework. This makes it difficult to understand the necessity of also reducing risk through vulnerability reduction and hazard mitigation. In fact, in this conceptual framework risk and vulnerability cannot be reduced directly. The arrows from vulnerability and hazards only point out into the direction of the risk analysis; the opportunity to reduce the vulnerabilities themselves is not explicitly shown. The figure underlines the fact that early warning, preparedness and response could reduce the disaster impact, even though a link between the risk factors (vulnerability and hazards) and the application of risk reduction measures is not included. Moreover, the conceptual framework does not give an answer as to whether exposure should be seen as a feature of the hazard or of the vulnerabilities. The UN/ISDR report Living with Risk (UN/ISDR, 2004) views physical vulnerability as the susceptibility of location. This may be interpreted as a sign that physical vulnerability encompasses spatial exposure, but no precise answer is given (UN/ISDR, 2004: 42). Furthermore, the report differentiates between coping capacity and capacity. While capacity is understood as all the strengths and resources available within a community, society or organisation that can reduce risk, the term coping capac- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 24) MEASURING VULNERABILITY 25 Figure 1.6 The ISDR framework for disaster risk reduction. Source: UN/ISDR, 2004. ity is defined as the way in which people or organisations use available resources and abilities to face adverse consequences of a disaster (UN/ISDR 2004: 16). This differentiation indicates that one has to consider the fact that potentially available capacities and applied capacities are different with regard to disaster risk reduction. Additionally, the UN/ISDR conceptual framework places vulnerability and the disaster risk reduction elements within a framework called the ‘‘sustainable development context’’ (Figure 1.6). This is meant to underline the necessity of linking risk reduction and sustainable development, which means risk reduction strategies should promote sustainable devel- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 25) 26 JÖRN BIRKMANN opment by making the best use of connections among social, economic and environmental goals to reduce risk (UN/ISDR, 2004: 18). Although it is important to link risk reduction with sustainable development, the perception that risk reduction is similar to and always compatible with sustainable development is inadequate. The general recommendation of ‘‘making the best use of connections among social, economic and environmental goals’’ is a sort of ill-defined ‘‘balancing exercise’’ between social, economic and environmental goals. In practice, vulnerability reduction and sustainable development are confronted with deeply rooted social, economic and environmental conflicts, which cannot be wished away through a simple balancing exercise. There is therefore a need to define more precisely what sustainable development and risk reduction have in common as well as where the differences are (see section Vulnerability and sustainable development). Vulnerability in the global environmental change community The conceptual framework developed by Turner et al. (2003), considered here as being a representative of the global environmental change community, defines vulnerability in a broader sense. Their definition and analytical framework of vulnerability encompasses exposure, sensitivity and resilience. Moreover, vulnerability is viewed in the context of a joint or coupled human–environmental system (Turner et al., 2003: 8075; Kasperson, 2005). In contrast to the disaster risk community, this conceptual framework of Turner et al. (2003) defines exposure, coping response, impact response and adaptation response explicitly as parts of vulnerability (Figure 1.7). The framework also takes into account the interaction of the multiple interacting perturbations, stressors and stresses. Another important difference between the frameworks discussed earlier and this one lies in the fact that the conceptual framework of Turner et al. examines vulnerability within the broader and closely linked human–environment context (Turner et al., 2003: 8076; Kasperson, 2005). The conceptual framework also takes into account the concept of adaptation, which is viewed as an element that increases resilience. This framework constitutes an interesting alternative to the conceptual frameworks discussed earlier. However, some questions remain, such as whether the distinction between drivers and consequences in this feedback-loop system is appropriate. The onion framework UNU-EHS has developed two different conceptual frameworks of vulnerability, the ‘‘onion framework’’ and the ‘‘BBC conceptual framework’’ (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 26) MEASURING VULNERABILITY 27 Figure 1.7 Turner et al.’s Vulnerability Framework. Source: Turner et al., 2003: 8076. (discussed below). The onion framework defines vulnerability with regard to different hazard impacts related to the economic sphere and the social sphere. The impact of a disaster and the vulnerability it reveals is illustrated by the example of floods. Analytically the framework distinguishes a reality axis and an opportunity axis. The reality axis shows that a flood event could affect the economic sphere and cause flood damage, while if the impact of the flood caused huge additional disruption in the social sphere, a disaster would occur (Figure 1.8). Economic assets can be replaced, but the disruption of the inner social sphere of a society would cause long-term injuries and losses, which in this model are primarily associated with the term vulnerability. Different capacities exist within the centre of the social sphere (C1–C3), which means that whether a flood event becomes a disaster or not depends almost as much on the preparedness and coping capacity of the affected society as on the nature of the flood event itself (Bogardi and Birkmann, 2004). While C1 shows the fact that although the social sphere is affected, adequate coping capacities still exist; an impact of the flood event on the inner circle of the social sphere C3, however, would imply that social capacities are entirely insuf- (AutoPDF V7 22/8 09:37) UNU (6.125!9.25") TimesL J-1589 Birkmann PMU: WSL 03/08/2006 PMU: WSL(W) 15/8/06 pp. 7–54 1589_01 (p. 27) 28 JÖRN BIRKMANN Figure 1.8 The onion framework. Source: Bogardi/Birkmann, 2004. ficient to deal with the flood event, thus precipitating the occurrence of a disaster (Bogardi and Birkmann, 2004). The ‘‘onion framework’’ relates the terms risk and vulnerability to potential losses and damages caused in the three different spheres. The framework emphasises that vulnerability deals with different ‘‘loss categories’’, such as economic and social losses. This means it stresses the fact that if a community’s or a person’s losses go beyond economic losses, for example extending to loss of confidence and trust, the flood event has reached the ‘‘intangible’’ assets. This implies a serious disruption of the functioning of the society to the point that vulnerability becomes evident. According to this framework, the more comprehensive concept of social vulnerability should incorporate the monetary dimension (likelihood of economic harm) as well as ‘‘intangibles’’ like confidence, trust and fear as potential consequences of the flood. Furthermore, the onion framework shows potenti...
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