Community-based approaches existed even before the existence of the state and its formal governance structure. People and communities used to help and take care of each other’s disaster needs. However, due to the evolution of state governance, new terminology of community-based disaster risk reduction (CBDRR) has been coined to help communities in an organized way. Different stakeholders are responsible for community-based actions; the two key players are the local governments and civil society, or nongovernment organizations. Private sector and academic and research institutions also play crucial roles in CBDRR. Many innovative CBDRR practices exist in the world, and it is important to analyze them and learn the common lessons. The key to community is its diversity, and this should be kept in mind for the CBDRR. There are different entry points and change agents based on the diverse community. It is important to identify the right change agent and entry point and to develop a sustainable mechanism to institutionalize CBDRR activities. Social networking needs to be incorporated for effective CBDRR.
Emergency and disaster planning involves a coordinated, co-operative process of preparing to match urgent needs with available resources. The phases are research, writing, dissemination, testing, and updating. Hence, an emergency plan needs to be a living document that is periodically adapted to changing circumstances and that provides a guide to the protocols, procedures, and division of responsibilities in emergency response. Emergency planning is an exploratory process that provides generic procedures for managing unforeseen impacts and should use carefully constructed scenarios to anticipate the needs that will be generated by foreseeable hazards when they strike. Plans need to be developed for specific sectors, such as education, health, industry, and commerce. They also need to exist in a nested hierarchy that extends from the local emergency response (the most fundamental level), through the regional tiers of government, to the national and international levels. Failure to plan can be construed as negligence because it would involve failing to anticipate needs that cannot be responded to adequately by improvisation during an emergency.
Plans are needed, not only for responding to the impacts of disaster, but also to maintain business continuity while managing the crisis, and to guide recovery and reconstruction effectively. Dealing with disaster is a social process that requires public support for planning initiatives and participation by a wide variety of responders, technical experts and citizens. It needs to be sustainable in the light of challenges posed by non-renewable resource utilization, climate change, population growth, and imbalances of wealth. Although, at its most basic level, emergency planning is little more than codified common sense, the increasing complexity of modern disasters has required substantial professionalization of the field. This is especially true in light of the increasing role in emergency response of information and communications technology. Disaster planners and coordinators are resource managers, and in the future, they will need to cope with complex and sophisticated transfers of human and material resources. In a globalizing world that is subject to accelerating physical, social, and economic change, the challenge of managing emergencies well depends on effective planning and foresight, and the ability to connect disparate elements of the emergency response into coherent strategies.
Fatalism about natural disasters hinders action to prepare for those disasters, and overcoming this fatalism is one key element to preparing people for these disasters. Research by Bostrom and colleagues shows that failure to act often reflects gaps and misconceptions in citizen’s mental models of disasters. Research by McClure and colleagues shows that fatalistic attitudes reflect people’s attributing damage to uncontrollable natural causes rather than controllable human actions, such as preparation. Research shows which precise features of risk communications lead people to see damage as preventable and to attribute damage to controllable human actions. Messages that enhance the accuracy of mental models of disasters by including human factors recognized by experts lead to increased preparedness. Effective messages also communicate that major damage in disasters is often distinctive and reflects controllable causes. These messages underpin causal judgments that reduce fatalism and enhance preparation. Many of these messages are not only beneficial but also newsworthy. Messages that are logically equivalent but are differently framed have varying effects on risk judgments and preparedness. The causes of harm in disasters are often contested, because they often imply human responsibility for the outcomes and entail significant cost.
Dennis John Parker
Humankind is becoming increasingly dependent on timely flood warnings. Dependence is being driven by an increasing frequency and intensity of heavy rainfall events, a growing number of disruptive and damaging floods, and rising sea levels associated with climate change. At the same time, the population living in flood-risk areas and the value of urban and rural assets exposed to floods are growing rapidly. Flood warnings are an important means of adapting to growing flood risk and learning to live with it by avoiding damage, loss of life, and injury. Such warnings are increasingly being employed in combination with other flood-risk management measures, including large-scale mobile flood barriers and property-level protection measures.
Given that lives may well depend on effective flood warnings and appropriate warning responses, it is crucial that the warnings perform satisfactorily, particularly by being accurate, reliable, and timely. A sufficiently long warning lead time to allow precautions to be taken and property and people to be moved out of harm’s way is particularly important. However, flood warnings are heavily dependent on the other components of flood forecasting, warning, and response systems of which they are a central part. These other components—flood detection, flood forecasting, warning communication, and warning response—form a system that is characterized as a chain, each link of which depends on the other links for effective outcomes. Inherent weaknesses exist in chainlike processes and are often the basis of warning underperformance when it occurs.
A number of key issues confront those seeking to create and successfully operate flood warning systems, including (1) translating technical flood forecasts into warnings that are readily understandable by the public; (2) taking legal responsibility for warnings and their dissemination; (3) raising flood-risk awareness; (4) designing effective flood warning messages; (5) knowing how best and when to communicate warnings; and (6) addressing uncertainties surrounding flood warnings.
Flood warning science brings together a large body of research findings from a particularly wide range of disciplines ranging from hydrometeorological science to social psychology. In recent decades, major advances have been made in forecasting fluvial and coastal floods. Accurately forecasting pluvial events that cause surface-water floods is at the research frontier, with significant progress being made. Over the same time period, impressive advances in a variety of rapid, personalized communication means has transformed the process of flood warning dissemination. Much is now known about the factors that constrain and aid appropriate flood warning responses both at the individual and at organized, flood emergency response levels, and a range of innovations are being applied to improve response effectiveness. Although the uniqueness of each flood and the inherent unpredictability involved in flood events means that sometimes flood warnings may not perform as expected, flood warning science is helping to minimize these occurrences.
Brett F. Sanders
Communities facing urban flood risk have access to powerful flood simulation software for use in disaster-risk-reduction (DRR) initiatives. However, recent research has shown that flood risk continues to escalate globally, despite an increase in the primary outcome of flood simulation: increased knowledge. Thus, a key issue with the utilization of urban flood models is not necessarily development of new knowledge about flooding, but rather the achievement of more socially robust and context-sensitive knowledge production capable of converting knowledge into action. There are early indications that this can be accomplished when an urban flood model is used as a tool to bring together local lay and scientific expertise around local priorities and perceptions, and to advance improved, target-oriented methods of flood risk communication.
The success of urban flood models as a facilitating agent for knowledge coproduction will depend on whether they are trusted by both the scientific and local expert, and to this end, whether the model constitutes an accurate approximation of flood dynamics is a key issue. This is not a sufficient condition for knowledge coproduction, but it is a necessary one. For example, trust can easily be eroded at the local level by disagreements among scientists about what constitutes an accurate approximation.
Motivated by the need for confidence in urban flood models, and the wide variety of models available to users, this article reviews progress in urban flood model development over three eras: (1) the era of theory, when the foundation of urban flood models was established using fluid mechanics principles and considerable attention focused on development of computational methods for solving the one- and two-dimensional equations governing flood flows; (2) the era of data, which took form in the 2000s, and has motivated a reexamination of urban flood model design in response to the transformation from a data-poor to a data-rich modeling environment; and (3) the era of disaster risk reduction, whereby modeling tools are put in the hands of communities facing flood risk and are used to codevelop flood risk knowledge and transform knowledge to action. The article aims to inform decision makers and policy makers regarding the match between model selection and decision points, to orient the engineering community to the varied decision-making and policy needs that arise in the context of DRR activities, to highlight the opportunities and pitfalls associated with alternative urban flood modeling techniques, and to frame areas for future research.
Vincenzo Bollettino, Tilly Alcayna, Philip Dy, and Patrick Vinck
In recent years, the notion of resilience has grown into an important concept for both scholars and practitioners working on disasters. This evolution reflects a growing interest from diverse disciplines in a holistic understanding of complex systems, including how societies interact with their environment. This new lens offers an opportunity to focus on communities’ ability to prepare for and adapt to the challenges posed by natural hazards, and the mechanism they have developed to cope and adapt to threats. This is important because repeated stresses and shocks still cause serious damages to communities across the world, despite efforts to better prepare for disasters.
Scholars from a variety of disciplines have developed resilience frameworks both to guide macro-level policy decisions about where to invest in preparedness and to measure which systems perform best in limiting losses from disasters and ensuring rapid recovery. Yet there are competing conceptions of what resilience encompasses and how best to measure it. While there is a significant amount of scholarship produced on resilience, the lack of a shared understanding of its conceptual boundaries and means of measurement make it difficult to demonstrate the results or impact of resilience programs.
If resilience is to emerge as a concept capable of aiding decision-makers in identifying socio-geographical areas of vulnerability and improving preparedness, then scholars and practitioners need to adopt a common lexicon on the different elements of the concept and harmonize understandings of the relationships amongst them and means of measuring them. This article reviews the origins and evolution of resilience as an interdisciplinary, conceptual umbrella term for efforts by different disciplines to tackle complex problems arising from more frequent natural disasters. It concludes that resilience is a useful concept for bridging different academic disciplines focused on this complex problem set, while acknowledging that specific measures of resilience will differ as different units and levels of analysis are employed to measure disparate research questions.
People not only want to be safe from natural hazards; they also want to feel they are safe. Sometimes these two desires pull in different directions, and when they do, this slows the journey to greater physical adaptation and resilience.
All people want to feel safe—especially in their own homes. In fact, although not always a place of actual safety, in many cultures “home” is nonetheless idealized as a place of security and repose. The feeling of having a safe home is one part of what is termed ontological security: freedom from existential doubts and the ability to believe that life will continue in much the same way as it always has, without threat to familiar assumptions about time, space, identity, and well-being. By threatening our homes, floods, earthquakes, and similar events disrupt ontological security: they destroy the possessions that support our sense of who we are; they fracture the social structures that provide us with everyday needs such as friendship, play, and affection; they disrupt the routines that give our lives a sense of predictability; and they challenge the myth of our immortality. Such events, therefore, not only cause physical injury and loss; by damaging ontological security, they also cause emotional distress and jeopardize long-term mental health.
However, ontological security is undermined not only by the occurrence of hazard events but also by their anticipation. This affects people’s willingness to take steps that would reduce hazard vulnerability. Those who are confident that they can eliminate their exposure to a hazard will usually do so. More commonly, however, the available options come with uncertainty and social/psychological risks: often, the available options only reduce vulnerability, and sometimes people doubt the effectiveness of these options or their ability to choose and implement appropriate measures. In these circumstances, the risk to ontological security that is implied by action can have greater influence than the potential benefits. For example, although installing a floodgate might reduce a business’s flood vulnerability, the business owner might feel that its presence would act as an everyday reminder that the business, and the income derived from it, are not secure. Similarly, bolting furniture to the walls of a home might reduce injuries in the next earthquake, but householders might also anticipate that it would remind them that there is a continual threat to their home. Both of these circumstances describe situations in which the anticipation of future feelings can tap into less conscious anxieties about ontological security.
The manner in which people anticipate impacts on ontological security has several implications for preparedness. For example, it suggests that hazard warnings will be counterproductive if they are not accompanied by suggestions of easy, reliable ways of eliminating risk. It also suggests that adaptation measures should be designed not to enhance awareness of the hazard.
Mahesh Prakash, James Hilton, Claire Miller, Vincent Lemiale, Raymond Cohen, and Yunze Wang
Remotely sensed data for the observation and analysis of natural hazards is becoming increasingly commonplace and accessible. Furthermore, the accuracy and coverage of such data is rapidly improving. In parallel with this growth are ongoing developments in computational methods to store, process, and analyze these data for a variety of geospatial needs. One such use of this geospatial data is for input and calibration for the modeling of natural hazards, such as the spread of wildfires, flooding, tidal inundation, and landslides. Computational models for natural hazards show increasing real-world applicability, and it is only recently that the full potential of using remotely sensed data in these models is being understood and investigated. Some examples of geospatial data required for natural hazard modeling include:
• elevation models derived from RADAR and Light Detection and Ranging (LIDAR) techniques for flooding, landslide, and wildfire spread models
• accurate vertical datum calculations from geodetic measurements for flooding and tidal inundation models
• multispectral imaging techniques to provide land cover information for fuel types in wildfire models or roughness maps for flood inundation studies
Accurate modeling of such natural hazards allows a qualitative and quantitative estimate of risks associated with such events. With increasing spatial and temporal resolution, there is also an opportunity to investigate further value-added usage of remotely sensed data in the disaster modeling context. Improving spatial data resolution allows greater fidelity in models allowing, for example, the impact of fires or flooding on individual households to be determined. Improving temporal data allows short and long-term trends to be incorporated into models, such as the changing conditions through a fire season or the changing depth and meander of a water channel.