You are looking at 51-60 of 68 articles
Humankind has always lived with natural hazards and their consequences. While the frequency and intensity of geological processes may have remained relatively stable, population growth and infrastructure development in areas susceptible to experiencing natural hazards has increased societal risk and the losses experienced from hazard activity. Furthermore, increases in weather-related (e.g., hurricanes, wildfires) hazards emanating from climate change will increase risk in some countries and result in others having to deal with natural hazard risk for the first time.
Faced with growing and enduring risk, disaster risk reduction (DRR) strategies will play increasingly important roles in facilitating societal sustainability. This article discusses how readiness or preparedness makes an important contribution to comprehensive DRR. Readiness is defined here in terms of those factors that facilitate people’s individual and collective capability to anticipate, cope with, adapt to, and recover from hazard consequences. This article first discusses the need to conceptualize readiness as comprising several functional categories (structural, survival/direct action, psychological, community/capacity building, livelihood and community-agency readiness).
Next, the article discusses how the nature and extent of people’s readiness is a function of the interaction between the information available and the personal, family, community and societal factors used to interpret information and support readiness decision-making. The health belief model (HBM), protection motivation theory (PMT), person-relative-to-event (PrE) theory, theory of planned behavior (TPB), critical awareness (CA), protective action decision model (PADM), and community engagement theory (CET) are used to introduce variables that inform people’s readiness decision-making. A need to consider readiness as a developmental process is discussed and identifies how the variables introduced in the above theories play different roles at different stages in the development of comprehensive readiness.
Because many societies must learn to coexist with several sources of hazard, an “all-hazards” approach is required to facilitate the capacity of societies and their members to be resilient in the face of the various hazard consequences they may have to contend with. This article discusses research into readiness for the consequences that arise from earthquake, volcanic, flood, hurricane, and tornado hazards. Furthermore, because hazards transcend national and cultural divides, a comprehensive conceptualization of readiness must accommodate a cross-cultural perspective. Issues in the cross-cultural testing of theory is discussed, as is the need for further work into the relationship between readiness and culture-specific beliefs and processes.
Guy J.-P. Schumann
For about 40 years, with a proliferation over the last two decades, remote sensing data, primarily in the form of satellite and airborne imagery and altimetry, have been used to study floods, floodplain inundation, and river hydrodynamics. The sensors and data processing techniques that exist to derive information about floods are numerous. Instruments that record flood events may operate in the visible, thermal, and microwave range of the electromagnetic spectrum. Due to the limitations posed by adverse weather conditions during flood events, radar (microwave range) sensors are invaluable for monitoring floods; however, if a visible image of flooding can be acquired, retrieving useful information from this is often more straightforward. During recent years, scientific contributions in the field of remote sensing of floods have increased considerably, and science has presented innovative research and methods for retrieving information content from multi-scale coverages of disastrous flood events all over the world. Progress has been transformative, and the information obtained from remote sensing of floods is becoming mature enough to not only be integrated with computer simulations of flooding to allow better prediction, but also to assist flood response agencies in their operations.
Furthermore, this advancement has led to a number of recent and upcoming satellite missions that are already transforming current procedures and operations in flood modeling and monitoring, as well as our understanding of river and floodplain hydrodynamics globally. Global initiatives that utilize remote sensing data to strengthen support in managing and responding to flood disasters (e.g., The International Charter, The Dartmouth Flood Observatory, CEOS, NASA’s Servir and the European Space Agency’s Tiger-Net initiatives), primarily in developing nations, are becoming established and also recognized by many nations that are in need of assistance because traditional ground-based monitoring systems are sparse and in decline. The value remote sensing can offer is growing rapidly, and the challenge now lies in ensuring sustainable and interoperable use as well as optimized distribution of remote sensing products and services for science as well as operational assistance.
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.
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Natural Hazard Science. Please check back later for the full article.
Attempts to manage natural hazards are undergoing considerable transformations. This includes the establishment of risk-based management approaches, the encouragement to govern natural hazards more inclusively, and the rising relevance of the concept of resilience. The benefits of this transformation are usually framed similarly: Risk-based approaches are regarded as a rational way of balancing the costs associated with mitigating the consequences of hazards and the anticipated benefits; inclusive modes of governing risks help to increase the acceptance and quality of management processes as well as its outcomes; and the concept of resilience is connoted positively since it demands a greater openness to uncertainties and aims at increasing the capacities of various actors to cope with radical surprises.
However, the increasing consideration of both concepts in policy and decision making processes is also associated with a changing demarcation between public and private responsibilities and with an altering relationship between organizations involved in the management process and the wider public: Establishing an inclusive risk governance mode means also to open up new avenues for the public to challenge the decisions made by responsible authorities.
To understand some of these dynamics a change of perspective is fruitful: Instead of asking how the concept of risk or resilience might be useful to improve the management and governance of natural hazards, it is helpful to understand how societies are governed by the concept of risk and resilience. Following this perspective, risk-based management approaches have predominantly a defensive function in deflecting blame and rationalizing policy choices ex ante by enabling managing organizations to more clearly define for which “risks” they are responsible (i.e., nonacceptable risks) and which are beyond their responsibility (i.e., acceptable risks). At the same time, this demarcation has also profound distributional effects as acceptable risks usually need to be mitigated individually and/or locally, raising the question of how to ensure the just sharing of the differently distributed benefits and burdens of risk-based approaches.
The concept of resilience plays in this context a paradoxical and, at the same time, complementary role: In its more operational interpretation (e.g., adaptive management), resilience-based management approaches can be in conflict with risk-based approaches, at least from an operational and policy making perspective as they pull those responsible for managing current and future flood risks in different directions: While the idea of resilience puts an emphasis on openness and flexibility, managing natural hazards that are risk based aims at ensuring the proportionality of costs and benefits usually by closing down uncertainties in order to transform them into calculable risks. At the same time, resilience-based governance approaches with their emphasis on self-organization and learning complement risk-based approaches in the sense that actors or communities that are exposed to “acceptable risks” are implicitly or explicitly made responsible for maintaining their resilience on their own, since the role of public authorities is usually restricted to an enabling one.
Recent extreme hydrological events (e.g., in the United States in 2005 or 2012, Pakistan in 2010, and Thailand in 2011) revealed increasing flood risks due to climate and societal change. Consequently, the roles of multiple stakeholders in flood risk management have transformed significantly. A central aspect here is the question of sharing responsibilities among global, national, regional, and local stakeholders in organizing flood risk management of all kinds. This new policy agenda of sharing responsibilities strives to delegate responsibilities and costs from the central government to local authorities, and from public administration to private citizens. The main reasons for this decentralization are that local authorities can deal more efficiently with public administration tasks concerned with risks and emergency management. Resulting locally based strategies for risk reduction are expected to tighten the feedback loops between complex environmental dynamics and human decision-making processes. However, there are a series of consequences to this rescaling process in flood risk management, regarding the development of new governance structures and institutions, like resilience teams or flood action groups in the United Kingdom. Additionally, downscaling to local-level tasks without additional resources is particularly challenging. This development has tightened further with fiscal and administrative cuts around the world resulting from the global economic crisis of 2007–2008, which tightening eventually causes budget restrictions for flood risk management. Managing local risks easily exceeds the technical and budgetary capacities of municipal institutions, and individual citizens struggle to carry the full responsibility of flood protection. To manage community engagement in flood risk management, emphasis should be given to the development of multi-level governance structures, so that multiple stakeholders share fairly the power, resources, and responsibility in disaster planning. If we fail to do so, some consequences would be: (1), “hollowing out” the government, including the downscaling of the responsibility towards local stakeholders; and (2), inability of the government to deal with the new tasks due to lack of resources transferred to local authorities.
Prediction of floods at locations where no streamflow data exist is a global issue because most of the countries involved don’t have adequate streamflow records. The United States Geological Survey developed the regional flood frequency (RFF) analysis to predict annual peak flow quantiles, for example, the 100-year flood, in ungauged basins. RFF equations are pure statistical characterizations that use historical streamflow records and the concept of “homogeneous regions.” To supplement the accuracy of flood quantile estimates due to limited record lengths, a physical solution is required. It is further reinforced by the need to predict potential impacts of a changing hydro-climate system on flood frequencies. A nonlinear geophysical theory of floods, or a scaling theory for short, focused on river basins and abandoned the “homogeneous regions” concept in order to incorporate flood producing physical processes. Self-similarity in channel networks plays a foundational role in understanding the observed scaling, or power law relations, between peak flows and drainage areas. Scaling theory of floods offers a unified framework to predict floods in rainfall-runoff (RF-RO) events and in annual peak flow quantiles in ungauged basins.
Theoretical research in the course of time clarified several key ideas: (1) to understand scaling in annual peak flow quantiles in terms of physical processes, it was necessary to consider scaling in individual RF-RO events; (2) a unique partitioning of a drainage basin into hillslopes and channel links is necessary; (3) a continuity equation in terms of link storage and discharge was developed for a link-hillslope pair (to complete the mathematical specification, another equation for a channel link involving storage and discharge can be written that gives the continuity equation in terms of discharge); (4) the self-similarity in channel networks plays a pivotal role in solving the continuity equation, which produces scaling in peak flows as drainage area goes to infinity (scaling is an emergent property that was shown to hold for an idealized case study); (5) a theory of hydraulic-geometry in channel networks is summarized; and (6) highlights of a theory of biological diversity in riparian vegetation along a network are given.
The first observational study in the Goodwin Creek Experimental Watershed, Mississippi, discovered that the scaling slopes and intercepts vary from one RF-RO event to the next. Subsequently, diagnostic studies of this variability showed that it is a reflection of variability in the flood-producing mechanisms. It has led to developing a model that links the scaling in RF-RO events with the annual peak flow quantiles featured here.
Rainfall-runoff models in engineering practice use a variety of techniques to calibrate their parameters using observed streamflow hydrographs. In ungagged basins, streamflow data are not available, and in a changing climate, the reliability of historic data becomes questionable, so calibration of parameters is not a viable option. Recent progress on developing a suitable theoretical framework to test RF-RO model parameterizations without calibration is briefly reviewed.
Contributions to generalizing the scaling theory of floods to medium and large river basins spanning different climates are reviewed. Two studies that have focused on understanding floods at the scale of the entire planet Earth are cited.
Finally, two case studies on the innovative applications of the scaling framework to practical hydrologic engineering problems are highlighted. They include real-time flood forecasting and the effect of spatially distributed small dams in a river network on real-time flood forecasting.
Avalanches have long been a natural threat to humans in mountainous areas. At the end of the Middle Ages, the population in Europe experienced significant growth, leading to an intensive exploitation of upper valleys. At almost the same time, Europe’s climate cooled down considerably and severe winters became more common. In the Alps, several villages were partly destroyed by avalanches, forcing inhabitants to develop the first mitigation strategies against the threat. By the late 19th century, the development of central administrations led to the creation of national forestry departments in each alpine country, principally to tackle the dangers posed by avalanches. As a result, forest engineers conceived not only the science of avalanches but also the first large-scale techniques to alleviate avalanche risks (such as reforestation). However, with the steady growth of transport, industry, tourism, and urbanization in high-altitude areas, these earlier measures soon reached their limits. A new impetus was then given to better forecasting avalanche activity and predicting the destructive potential of extreme avalanches. Avalanche zoning, snowfall forecasts, avalanche-dynamics models, and new protection systems for the protection of structures and inhabitants have become increasingly more common since World War II.
With the advent of personal computers and the increasing sophistication of computational resources, it has become easier to predict the behavior of avalanches and protect threatened areas accordingly. The success of this research and the protection policies implemented since World War II are reflected in the drastic reduction in the number of disasters affecting dwellings in the Alps (most deaths by avalanche now occur during recreational activities). Significant progress has been made since the 1980s, leading to a better understanding of avalanche behavior and the mediation of associated risks. Yet we should not assume that this progress is steady or that our capacity to control such hazards is more advanced than it was two decades ago. Efforts to predict avalanches contrast with work in other sciences such as meteorology, for which forecasts have become increasingly more reliable with advancements in computational power. Explaining the difference is simple: in meteorology, the material is air, a substance whose behavior is well known. The main difficulty lies in the computation of enormous volumes of air encountering various flow and temperature conditions. For avalanches, the material is snow, a subtle mixture of water (in different forms) and air, whose behavior is remarkably complex. Modern models of avalanche dynamics are able to predict this behavior with varying degrees of success.
Daniel P. Aldrich
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Natural Hazard Science. Please check back later for the full article.
The impact of natural disasters continues to grow in the early 21st century, as extreme weather events become more frequent and population density in vulnerable coastal and inland cities increases. Against this backdrop of risk, decision-makers persist in focusing primarily on structural measures to reduce losses centered on physical infrastructure, such as berms, sea walls, retrofitted buildings, and levees. Yet a growing body of research emphasizes that strengthening social infrastructure, not just physical infrastructure, serves as a cost-effective way to improve communities’ ability to withstand and rebound from disasters. Three distinct kinds of social connections, including bonding, bridging, and linking social ties, support resilience through increasing the provision of emergency information, mutual aid, and collective action within communities to address natural hazards before, during, and after disaster events. Investing in social capital fosters community resilience that transcends natural hazards and positively affects collective governance and community health.
Social capital has a long history in social science research, and scholarship discussing it has grown within various disciplines. Broadly, the term describes the way that social ties generate norms of reciprocity and trust, allow collective action, build solidarity, and foster information and resource flows among people. From education to crime, social capital has been shown to have positive impacts on individual and community outcomes, and research in natural hazards has similarly shown positive outcomes for individual and community resilience. Social capital can also foster negative outcomes, however, including exclusionary practices, corruption, and increased inequality. Understanding which types of social capital are most useful for increasing resilience is important to move the natural hazards field forward.
Many questions about social capital and natural hazards remain partially answered at best. Do different types of social capital matter at different stages of disaster (e.g., mitigation, preparedness, response, and recovery)? How do social capital’s effects vary across cultural contexts and stratified groups? What measures of social capital are available to practitioners and scholars? What actions are available to decision-makers seeking to invest in the social infrastructure of communities vulnerable to natural hazards? Which programs and interventions have shown merit through field tests? What outcomes can decision-makers anticipate with these investments? Where can scholars find data sets on resilience and social capital? Beginning with the classics in social capital theory and moving to the frontier of disaster and resilience studies, this discussion illuminates the current state of knowledge in this area and addresses future research needs.
Philip Bubeck, Antje Otto, and Juergen Weichselgartner
Floods remain the most devastating natural hazard globally, despite substantial investments in flood prevention and management in recent decades. Fluvial floods, such as the ones in Pakistan in 2010 and Thailand in 2011, can affect entire countries and cause severe economic and human losses. Also, coastal floods can inflict substantial harm owing to their destructive forces in terms of wave and tidal energy. A flood type that received growing attention in recent years is flooding from pluvial events (heavy rainfall). Even though these are locally confined, their sudden onset and unpredictability pose a danger to areas that are generally not at risk from flooding. In the future, it is projected that flood risk will increase in many regions both because of the effects of global warming on the hydrological cycle and the continuing concentration of people and economic assets in risk-prone areas.
Floods have a large variety of societal impacts that span across space and time. While some of these impacts are obvious and have been well researched, others are more subtle and less is known about their complex processes and long-term effects. The most immediate and apparent impact of floods is direct damage caused by physical contact between floodwaters and economic assets, cultural heritage, or human beings, with the result for humans being injuries and deaths. Direct flood damage can amount to billions of US dollars for single events, such as the floods in the Danube and Elbe catchment in Central Europe in 2002 and 2013. More indirect economic implications are the losses that occur outside of the flood event in space and time, such as losses due to business disruption. The flood in Thailand in 2011, for instance, resulted in a lack of auto parts supplies and consequently the shutdown of car manufacturing within and outside the flood zone.
Floods also have long-term indirect impacts on flood-affected people and communities. Experiencing property damage and losing important personal belongings can have a negative psychological effect on flood victims. Much less is known about this type of flood impact: how long do these impacts last? What makes some people or communities recover faster than others from financial losses and emotional stress? Moreover, flood impacts are not equally distributed across different groups of society. Often, poor, elderly, and marginalized societal groups are particularly vulnerable to the effects of flooding inasmuch as these groups generally have little social, human, and financial coping capacities. In many countries, women regularly bear a disproportionately high burden because of their societal status.
Finally, severe floods often provide so-called windows of opportunities, enabling rapid policy change, resulting in new flood risk management policies. Such newly adopted policy arrangements can lead to societal conflicts over issues of interests, equity, and fairness. For instance, flood events often trigger large-scale investment in flood defense infrastructure, which are associated with high construction costs. Although these costs are usually borne by the taxpayer, often only a small proportion of society shares in their benefits. In addition, societal conflict can arise concerning where to build structural measures; what impacts these measures have on the ground regarding economic development potentials, different kinds of uses, and nature protection; and which effects are expected downstream. In such controversies, issues of participation and decision making are central and often highly contested.
While floods are usually associated with negative societal impacts in industrialized countries, they also have beneficial impacts on nature and society. In many parts of the world, the livelihood of millions of people depends on the recurring occurrence of flooding. For instance, farming communities in or near floodplains rely upon regular floodwaters that carry nutrients and sediments, enriching the soil and making it fertile for cultivation.
Stephanie E. Chang
Infrastructure systems—sometimes referred to as critical infrastructure or lifelines—provide services such as energy, water, sanitation, transportation, and communications that are essential for social and economic activities. Moreover, these systems typically serve large populations and comprise geographically extensive networks. They are also highly interdependent, so outages in one system such as electric power or telecommunications often affect other systems. As a consequence, when infrastructure systems are damaged in disasters, the ensuing losses are often substantial and disproportionately large. Collapse of a single major bridge, for example, can disrupt traffic flows over a broad region and impede emergency response, evacuation, commuting, freight movement, and economic recovery. Power outages in storms and other hazard events can affect millions of people, shut down businesses, and even cause fatalities. Infrastructure outages typically last from hours to weeks but can extend for months or even years. Minimizing disruptions to infrastructure services is thus key to enhancing communities’ disaster resilience.
Research on infrastructure systems in natural hazards has been growing, especially as major disasters provide new data, insights, and urgency to the problem. Engineering advances have been made in understanding how hazard stresses may damage the physical components of infrastructure systems such as pipes and bridges, as well as how these elements can be designed to better withstand hazards. Modeling studies have assessed how physical damage disrupts the provision of services—for example, by indicating which neighborhoods in an urban area may be without potable water—and how disruption can be reduced through engineering and planning. The topic of infrastructure interdependencies has commanded substantial research interest.
Alongside these developments, social science and interdisciplinary research has also been growing on the important topic of how infrastructure disruption in disasters has affected populations and economies. Insights into these impacts derive from a variety of information sources, including surveys, field observations, analysis of secondary data, and computational models. Such research has established the criticality of electric power and water services, for example, and the heightened vulnerability of certain population groups to infrastructure disruption. Omitting the socioeconomic impacts of infrastructure disruptions can lead to underinvestment in disaster mitigation. While the importance of understanding and reducing infrastructure disruption impacts is well-established, many important research gaps remain.