Allison Hoadley Anderson
In architecture, mitigation reduces the magnitude of climate change by reducing demand for resources; anticipatory adaptation improves performance against hazards; and planned adaptation creates policies and codes to support adaptation.
Adaptation prepares for a future with intensifying climate conditions. The built environment must prepare for challenges that may be encountered during the service life of the building, and reduce human exposure to hazards. Structures are responsible for about 39% of the primary energy consumption worldwide and 24% of the greenhouse gas emissions, significantly contributing to the causes of climate change. Measures to reduce demand in the initial construction and over the life cycle of the building operation directly impact the climate.
Improving performance against hazards requires a suite of modifications to counter specific threats. Adaptation measures may address higher temperatures, extreme precipitation, stormwater flooding, sea-level rise, hurricanes, drought, soil subsidence, wildfires, extended pest ranges, and multiple hazards. Because resources to meet every threat are inadequate, actions with low costs now which offer high benefits under a range of predicted future climates become high-priority solutions.
Disaster risk is also reduced by aligning policies for planning and construction with anticipated hazards. Climate adaptation policies based on the local effects of climate change are a new tool to communicate risk and share resources. Building codes establish minimum standards for construction, so incorporating adaptation strategies into codes ensures that the resulting structures will survive a range of uncertain futures.
Rob A. DeLeo
Agenda setting describes the process through which issues are selected for consideration by a decision-making body. Among the myriad of issues policymakers can consider, few are more vexing than natural hazards. By aggregating (or threatening to aggregate) death, destruction, and economic loss, natural hazards represent a serious and persistent threat to public safety. While citizens rightfully expect policymakers to protect them, many of the policy challenges associated natural hazards fail to reach the crowded government agenda. This article reviews the literature on agenda setting and natural hazards, including the strain between preparing for emerging hazards, on the one hand, and responding to existing disasters, on the other hand. It considers the extent to which natural hazards pose distinctive difficulties during the agenda-setting process, focusing specifically on the dynamics of issue identification, problem definition, venue shopping, and interest group mobilization in natural hazard domains. It closes by suggesting a number of future avenues of agenda-setting research.
Brenden Jongman, Hessel C. Winsemius, Stuart A. Fraser, Sanne Muis, and Philip J. Ward
The flooding of rivers and coastlines is the most frequent and damaging of all natural hazards. Between 1980 and 2016, total direct damages exceeded $1.6 trillion, and at least 225,000 people lost their lives. Recent events causing major economic losses include the 2011 river flooding in Thailand ($40 billion) and the 2013 coastal floods in the United States caused by Hurricane Sandy (over $50 billion). Flooding also triggers great humanitarian challenges. The 2015 Malawi floods were the worst in the country’s history and were followed by food shortage across large parts of the country.
Flood losses are increasing rapidly in some world regions, driven by economic development in floodplains and increases in the frequency of extreme precipitation events and global sea level due to climate change. The largest increase in flood losses is seen in low-income countries, where population growth is rapid and many cities are expanding quickly. At the same time, evidence shows that adaptation to flood risk is already happening, and a large proportion of losses can be contained successfully by effective risk management strategies. Such risk management strategies may include floodplain zoning, construction and maintenance of flood defenses, reforestation of land draining into rivers, and use of early warning systems.
To reduce risk effectively, it is important to know the location and impact of potential floods under current and future social and environmental conditions. In a risk assessment, models can be used to map the flow of water over land after an intense rainfall event or storm surge (the hazard). Modeled for many different potential events, this provides estimates of potential inundation depth in flood-prone areas. Such maps can be constructed for various scenarios of climate change based on specific changes in rainfall, temperature, and sea level.
To assess the impact of the modeled hazard (e.g., cost of damage or lives lost), the potential exposure (including buildings, population, and infrastructure) must be mapped using land-use and population density data and construction information. Population growth and urban expansion can be simulated by increasing the density or extent of the urban area in the model. The effects of floods on people and different types of buildings and infrastructure are determined using a vulnerability function. This indicates the damage expected to occur to a structure or group of people as a function of flood intensity (e.g., inundation depth and flow velocity).
Potential adaptation measures such as land-use change or new flood defenses can be included in the model in order to understand how effective they may be in reducing flood risk. This way, risk assessments can demonstrate the possible approaches available to policymakers to build a less risky future.
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.
Evolution of Strategic Flood Risk Management in Support of Social Justice, Ecosystem Health, and Resilience
Throughout history, flood management practice has evolved in response to flood events. This heuristic approach has yielded some important incremental shifts in both policy and planning (from the need to plan at a catchment scale to the recognition that flooding arises from multiple sources and that defenses, no matter how reliable, fail). Progress, however, has been painfully slow and sporadic, but a new, more strategic, approach is now emerging.
A strategic approach does not, however, simply sustain an acceptable level of flood defence. Strategic Flood Risk Management (SFRM) is an approach that relies upon an adaptable portfolio of measures and policies to deliver outcomes that are socially just (when assessed against egalitarian, utilitarian, and Rawlsian principles), contribute positively to ecosystem services, and promote resilience. In doing so, SFRM offers a practical policy and planning framework to transform our understanding of risk and move toward a flood-resilient society. A strategic approach to flood management involves much more than simply reducing the chance of damage through the provision of “strong” structures and recognizes adaptive management as much more than simply “wait and see.” SFRM is inherently risk based and implemented through a continuous process of review and adaptation that seeks to actively manage future uncertainty, a characteristic that sets it apart from the linear flood defense planning paradigm based upon a more certain view of the future.
In doing so, SFRM accepts there is no silver bullet to flood issues and that people and economies cannot always be protected from flooding. It accepts flooding as an important ecosystem function and that a legitimate ecosystem service is its contribution to flood risk management. Perhaps most importantly, however, SFRM enables the inherent conflicts as well as opportunities that characterize flood management choices to be openly debated, priorities to be set, and difficult investment choices to be made.
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.
Atta-ur Rahman, Shakeel Mahmood, Mohammad Dawood, and Fang Chen
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.
Hindu Kush is a high mountain system located in the immediate west of Karakorum and Himalayas. It is the greatest watershed of River Kabul, River Chitral, River Swat, and River Panjkora in Pakistan and the Amu River in Central Asia. The Hindu Kush system hosts numerous glaciers, snow-clad mountains, and fertile river valleys; it also supports a large population and provides year-round water to replenish streams and rivers. The study region is vulnerable to a wide range of hazards including floods, earthquakes, landslides, drought, and desertification. However, in the Hindu Kush region, riverine and flash floods frequently occur as well as extreme hydro-meteorological events. The upper reaches experience characteristics of flash floods, whereas the lower reaches experience river floods. In the upstream areas, flash floods are sudden and more destructive in nature. Every year in summer, monsoonal rainfall, together with the heavy melting of snow, ice, and glaciers accelerates discharge in rivers. Climate change has a strong relationship with trends in temperature and resultant changes in rainfall pattern and river discharge. In the wake of observed climate change, there is a rising trend in temperature, which indicates the early and rapid melting of snow and glaciers in the catchment areas. The analysis reveals that in the late 20th and early 21st centuries a radical change in behavior of numerous valley glaciers has been noted. Similarly, a fluctuation in the amount of snowfall occurrences together with its timing and seasonality has been recorded. In addition, the spatial and temporal scales of violent weather events have grown during the past thirty years. Such changes in water regimes including the frequent but substantial increase in heavy precipitation events and rapid melting of snow in the headwater region, siltation in active channels, excessive deforestation in the past three decades, human encroachments onto the active flood channel and the bursting of temporary dams have further escalated the flooding events. Analysis reveals that the Hindu Kush region is beyond the reach of existing weather RADAR network and hence flood forecasting and early warning is ineffective. In the study region, almost every year, the floodwater overflows the levees and causes damages to standing crops, infrastructure, sources of livelihood. And worst of all, there are human casualties.
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.
Tropical cyclones (TCs) in their most intense expression (hurricanes or typhoons) are the main natural hazards known to humankind. The impressive socioeconomic consequences for countries dealing with TCs make our ability to model these organized convective structures a key issue to better understanding their nature and their interaction with the climate system. The destructive effects of TCs are mainly caused by three factors: strong wind, storm surge, and extreme precipitation. These TC-induced effects contribute to the annual worldwide damage of the order of billions of dollars and a death toll of thousands of people. Together with the development of tools able to simulate TCs, an accurate estimate of the impact of global warming on TC activity is thus not only of academic interest but also has important implications from a societal and economic point of view. The aim of this article is to provide a description of the TC modeling implementations available to investigate present and future climate scenarios.
The two main approaches to dynamically model TCs under a climate perspective are through hurricane models and climate models. Both classes of models evaluate the numerical equations governing the climate system. A hurricane model is an objective tool, designed to simulate the behavior of a tropical cyclone representing the detailed time evolution of the vortex. Considering the global scale, a climate model can be an atmosphere (or ocean)-only general circulation model (GCM) or a fully coupled general circulation model (CGCM). To improve the ability of a climate model in representing small-scale features, instead of a general circulation model, a regional model (RM) can be used: this approach makes it possible to increase the spatial resolution, reducing the extension of the domain considered. In order to be able to represent the tropical cyclone structure, a climate model needs a sufficiently high horizontal resolution (of the order of tens of kilometers) leading to the usage of a great deal of computational power.
Both tools can be used to evaluate TC behavior under different climate conditions. The added value of a climate model is its ability to represent the interplay of TCs with the climate system, namely two-way relationships with both atmosphere and ocean dynamics and thermodynamics. In particular, CGCMs are able to take into account the well-known feedback between atmosphere and ocean components induced by TC activity and also the TC–related remote impacts on large-scale atmospheric circulation.
The science surrounding TCs has developed in parallel with the increasing complexity of the mentioned tools, both in terms of progress in explaining the physical processes involved and the increased availability of computational power. Many climate research groups around the world, dealing with such numerical models, continuously provide data sets to the scientific community, feeding this branch of climate change science.
Snow- and ice-related hazardous processes threaten society in tropical to high-latitude mountain areas worldwide and at highly variable time scales. On the one hand, small snow avalanches are recorded in high numbers every winter. On the other hand, glacial lake outburst floods (GLOFs) or large-scale volcano–ice interactions occur less frequently but may evolve into destructive process chains resulting in major disasters. These extreme examples document the huge field of types, magnitudes, and frequencies of snow- and ice-related hazardous processes.
Mountain societies have learned to cope with natural hazards for centuries, guided by personal experiences and oral and written tradition. Historical records are today still important as a basis to mitigate snow- and ice-related hazards. They are complemented by a broad array of observation and modeling techniques. These techniques differ among themselves with regard to (1) the type of process under investigation and (2) the scale and purpose of investigation. Multi-scale monitoring and warning systems for snow avalanches are in operation in densely populated mid-latitude mountain areas. They build on meteorological and snow profile data in combination with a large pool of expert knowledge.
In contrast, ice-related processes such as ice- or rock-ice avalanches, GLOFs, or associated process chains cause damage less frequently in space and time, so that societies are less well adapted. Even though the hazard sources are often far from the society—making field observation challenging—flows travelling for tens of kilometers sometimes impact populated areas. These hazards are strongly influenced by climate change–induced glacier and permafrost dynamics. On the regional or national scale, the evolution of such hazards has to be monitored at short intervals through aerial and satellite imagery and terrain data, employing geographic information systems (GIS). Known hazardous situations have to be monitored in the field.
Physical models—applied either in the laboratory or at real-world sites—are employed to explore the mobility of hazardous processes. Since the 1950s, however, computer models have increasingly gained importance in exploring possible travel distances, impact areas, velocities, and impact forces of events. While simple empirical-statistical approaches are used at broad scales in combination with GIS, advanced numeric models are applied to analyze specific case studies. However, the input parameters for these models are uncertain so that (1) the model results have to be validated with observations and (2) appropriate strategies to deal with the uncertainties have to be applied before using the model results for hazard zoning or dimensioning of protective structures. Due to rapid atmospheric warming and related changes in the cryosphere, hazard situations beyond historical experiences are expected to be increasingly relevant in the future. Scenario-based modeling of complex systems and process chains therefore represents an emerging research direction.