Seth Guikema and Roshanak Nateghi
Natural disasters can have significant widespread impacts on society, and they often lead to loss of electric power for a large number of customers in the most heavily impacted areas. In the United States, severe weather and climate events have been the leading cause of major outages (i.e., more than 50,000 customers affected), leading to significant socioeconomic losses. Natural disaster impacts can be modeled and probabilistically predicted prior to the occurrence of the extreme event, although the accuracy of the predictive models will vary across different types of disasters. These predictions can help utilities plan for and respond to extreme weather and climate events, helping them better balance the costs of disaster responses with the need to restore power quickly. This, in turn, helps society recover from natural disasters such as storms, hurricanes, and earthquakes more efficiently. Modern Bayesian methods may provide an avenue to further improve the prediction of extreme event impacts by allowing first-principles structural reliability models to be integrated with field-observed failure data.
Climate change and climate nonstationarity pose challenges for natural hazards risk assessment, especially for hydrometeorological hazards such as tropical cyclones and floods, although the link between these types of hazards and climate change remains highly uncertain and the topic of many research efforts. A sensitivity-based approach can be taken to understand the potential impacts of climate change-induced alterations in natural hazards such as hurricanes. This approach gives an estimate of the impacts of different potential changes in hazard characteristics, such as hurricane frequency, intensity, and landfall location, on the power system, should they occur. Further research is needed to better understand and probabilistically characterize the relationship between climate change and hurricane intensity, frequency, and landfall location, and to extend the framework to other types of hydroclimatological events.
Underlying the reliability of power systems in the United States is a diverse set of regulations, policies, and rules governing electric power system reliability. An overview of these regulations and the challenges associated with current U.S. regulatory structure is provided. Specifically, high-impact, low-frequency events such as hurricanes are handled differently in the regulatory structure; there is a lack of consistency between bulk power and the distribution system in terms of how their reliability is regulated. Moreover, the definition of reliability used by the North American Reliability Corporation (NERC) is at odds with generally accepted definitions of reliability in the broader reliability engineering community. Improvements in the regulatory structure may have substantial benefit to power system customers, though changes are difficult to realize.
Overall, broader implications are raised for modeling other types of natural hazards. Some of the key takeaway messages are the following: (1) the impacts natural hazard on infrastructure can be modeled with reasonable accuracy given sufficient data and modern risk analysis methods; (2) there are substantial data on the impacts of some types of natural hazards on infrastructure; and (3) appropriate regulatory frameworks are needed to help translate modeling advances and insights into decreased impacts of natural hazards on infrastructure systems.
Daniel P. Aldrich, Michelle A. Meyer, and Courtney M. Page-Tan
The impact of 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, seawalls, 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 the ability of communities 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, particularly in how it has grown within various disciplines. Broadly, the term describes how 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 also can foster negative outcomes, 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, at best, partially answered. 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? The current state of knowledge about social capital in disaster resilience provides guidance about supporting communities toward more resilience.
Collaboration and Cross-Sector Coordination for Humanitarian Assistance in a Disaster Recovery Setting
While known to be important and essential for improved effectiveness and efficiency, cross-sector coordination and collaboration among different actors engaged in postdisaster recovery is fraught with complications. Among the challenges are (a) who leads, and how; (b) the capacity and roles of the host government; (c) governance structures within organizations (which may differ a great deal); (d) assumptions of power; (e) the trade-off between valuing relationships and “getting the job done”; and (f) the varying constraints (and opportunities) of accountability. Recognizing the need to improve joint actions for a better response, the Humanitarian Reform Agenda (HRA), begun in 2005, led to the remolding of collective models of disaster response and the adoption of the global cluster system, which is essentially organized around the delivery of goods and services (sectors) by traditional aid actors such as the United Nations (UN), nongovernmental organizations (NGOs), and the International Red Cross and Red Crescent Movement. While the cluster system has largely been acknowledged as an improvement in collaboration among actors, a perennial challenge of cross-sector coordination remains. One of the opportunities for improvement lies in better and more predictable leadership, one of the key areas identified by the HRA. Another opportunity lies in changing the focus from a supply-driven approach of prioritizing what aid providers deliver to a demand-driven understanding, such as that offered by area-based approaches, wherein sectors are more closely aligned.
A common form of collaboration within aid is partnership between various actors (e.g., the United Nations or NGOs). Partnerships assume more than a constructing relationship: Effective partnerships emphasize the need for transparency and equity, along with being results-oriented and competent. Recognizing this, the Grand Bargain, resulting from the World Humanitarian Summit, noted that aid providers should engage with local and national responders in a spirit of partnership and aim to reinforce rather than replace local and national capacities.
Partnerships, however, fall short all too often, especially when one partner has power over the other, which is often the case. The report Time to Let Go, by the Overseas Development Institute (ODI), notes, for instance, that “the relationships between donor and implementer, aid provider and recipient, remain controlling and asymmetrical, and partnerships and interactions remain transactional and competitive, rather than reciprocal and collective.” The challenge remains to achieve the task at hand, while at the same time engaging in effective collaborative mechanisms that value the nature of the relationship. If this is not achieved, effective postdisaster recovery can be jeopardized.
Economic resilience, in its static form, refers to utilizing remaining resources efficiently to maintain functionality of a household, business, industry, or entire economy after a disaster strikes, and, in its dynamic form, to effectively investing in repair and reconstruction to promote accelerated recovery. As such, economic resilience is oriented to implementing various post-disaster actions (tactics) to reduce business interruption (BI), in contrast to pre-disaster actions such as mitigation that are primarily oriented to preventing property damage. A number of static resilience tactics have been shown to be effective (e.g., conserving scarce inputs, finding substitutes from within and from outside the region, using inventories, and relocating activity to branch plants/offices or other sites). Efforts to measure the effectiveness of the various tactics are relatively new and aim to translate these estimates into dollar benefits, which can be juxtaposed to estimates of dollar costs of implementing the tactics. A comprehensive benefit-cost analysis can assist public- and private sector decision makers in determining the best set of resilience tactics to form an overall resilience strategy.
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.
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.
Janine M. H. Selendy
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.
Increasingly frequent and intense extreme climatic events are wreaking havoc in regions all over the world, not only causing immediate death and destruction, but also destroying prospects for attaining the most basic of human needs—water, food, and secure shelter. What is more, the problems brought about by extreme events are often exacerbated by ecosystem destruction due to human activities. This is a universal, global problem. Children are the most vulnerable. Insufficient and polluted water afflicts a third or more of the people of the world causing over a billion illnesses, illnesses often related to 2.5 billion people lacking sanitation, and illnesses often combined with malnutrition. In 2013, 783 million people lacked clean water. Procurement and allocation of water are major problems in rural and urban areas. More than 70% of fresh water is used for irrigation of crops, much of it lost to evaporation, and much resulting in build up of salinization on bordering farmland. Cities, now home to 54% of the world’s population, often lack adequate infrastructure to provide clean drinking water. In the United States, cities are faced with contaminated water from their pipes, as in Flint Michigan and in New Jersey schools. Naturally occurring water pollutants that can harm ecosystems, aquatic organisms, and humans are becoming more prevalent due to physical developments and climate change. For example, toxic cyanobacteria, also known as blue-green algae, in coastal and inland waters are causing mortality and morbidity in humans, livestock, and wild animals. Over the last three decades, one of these bacteria, C. raciborskii has been increasingly recognized as a public health exigency for drinking water supplies across all inhabited continents.
While food today is more readily available worldwide than in the past, nearly a billion people go hungry. The roughly billion people who rely on fish from the oceans are faced with dwindling harvests due to overfishing, warming waters that harm coral reef breeding grounds, and the loss of mangrove spawning grounds. Crops and livestock are hurt by climate change. Productivity is diminished by reliance on monoculture, poor storage, and transportation problems. The situation is drastically worsened by unnecessary waste and spoilage. The world is producing more than enough food, according to the Food and Agriculture Organization of the United Nations, which says that “Recovering just half of what is lost or wasted” alone could feed the world. Regarding spoilage, aflatoxins—poisonous, cancer-causing chemicals produced by certain molds—are found in spoiled food, including staples such as corn, millet, peanuts, and wheat, affecting not only immediate consumers, but also those who buy processed food. Droughts causing dead livestock and wilted crops have driven millions from their homes and farmland, as happened in Syria. Subsequent conflict led millions of Syrians to become both political and climate refugees, living in refugee camps and traveling thousands of treacherous miles to resettle. Poverty, whether experienced in slums, refugee camps, or other rural and urban settings, causes lack of land and shortages of material for soundly built housing that can withstand weather changes, even screens to help reduce exposure to mosquitoes, flies, and other disease vectors. The nearly quarter of the world’s urban population who live in slums live mostly in overcrowded, unsafe shelters that lack structural security, water for drinking, cooking, and hygiene, and sanitation. They are exposed to communicable diseases and suffer mental stress. Community space, adequate education, and chances for employment or a way out of the slums are rare. In numerous coastal communities, houses are endangered by extreme weather conditions exasperated by climate change. The sea’s rise in India has caused river delta islands to vanish. In 2016, the first climate refugees in the United States, an entire community of Native American Indians, are being forced to move from their ancestral homes on Isle de Jean Charles, Louisiana. The present challenges are aggravated by climate change, population growth, and forced migration. It is critical to focus on these basic, inextricably interlocked needs for water, food, and secure shelter, with a view to preventive measures, and to do so with extreme sensitivity to cultures, communities, ecosystems, and ramifications to human health.