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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.

Article

Space weather is a collective term for different solar or space phenomena that can detrimentally affect technology. However, current understanding of space weather hazards is still relatively embryonic in comparison to terrestrial natural hazards such as hurricanes, earthquakes, or tsunamis. Indeed, certain types of space weather such as large Coronal Mass Ejections (CMEs) are an archetypal example of a low-probability, high-severity hazard. Few major events, short time-series data, and the lack of consensus regarding the potential impacts on critical infrastructure have hampered the economic impact assessment of space weather. Yet, space weather has the potential to disrupt a wide range of Critical National Infrastructure (CNI) systems including electricity transmission, satellite communications and positioning, aviation, and rail transportation. In the early 21st century, there has been growing interest in these potential economic and societal impacts. Estimates range from millions of dollars of equipment damage from the Quebec 1989 event, to some analysts asserting that losses will be in the billions of dollars in the wider economy from potential future disaster scenarios. Hence, the origin and development of the socioeconomic evaluation of space weather is tracked, from 1989 to 2017, and future research directions for the field are articulated. Since 1989, many economic analyzes of space weather hazards have often completely overlooked the physical impacts on infrastructure assets and the topology of different infrastructure networks. Moreover, too many studies have relied on qualitative assumptions about the vulnerability of CNI. By modeling both the vulnerability of critical infrastructure and the socioeconomic impacts of failure, the total potential impacts of space weather can be estimated, providing vital information for decision makers in government and industry. Efforts on this subject have historically been relatively piecemeal, which has led to little exploration of model sensitivities, particularly in relation to different assumption sets about infrastructure failure and restoration. Improvements may be expedited in this research area by open-sourcing model code, increasing the existing level of data sharing, and improving multidisciplinary research collaborations between scientists, engineers, and economists.

Article

Mountain environments, home to about 12% of the global population and covering nearly a quarter of the global land surface, create hazardous conditions for various infrastructures. The economic and ecologic importance of these environments for tourism, transportation, hydropower generation, or natural resource extraction requires that direct and indirect interactions between infrastructures and geohazards be evaluated. Construction of infrastructure in mountain permafrost environments can change the ground thermal regime, affect gravity-driven processes, impact the strength of ice-rich foundations, or result in permafrost aggradation via natural convection. The severity of impact, and whether permafrost will degrade or aggrade in response to the construction, is a function of numerous parameters including climate change, which needs to be considered when evaluating the changes in existing or formation of new geohazards. The main challenge relates to the uncertainties associated with the projections of medium- (decadal) and long-term (century-scale) climate change. A fundamental understanding of the various processes at play and a good knowledge of the foundation conditions is required to ascertain that infrastructure in permafrost environment functions as intended. Many of the tools required for identifying geohazards in the periglacial and appropriate risk management strategies are already available.

Article

Marta Borowska-Stefańska and Szymon Wiśniewski

Floods, which are among the most dangerous and frequent disasters in the world, are expected to occur more frequently due to climate change. Floods, and flash floods in particular, generate economic, environmental, and social effects. Economic effects include damage to infrastructure, the negative influence upon transportation and communications networks, and an increase in fuel costs, as well as time loss due to traffic delays (congestion) and the necessity of taking alternative routes. It is therefore important to take action both to prevent and to mitigate these effects. In the 21st century there has been a radical change in the approach to the issue of flood protection (as seen in the approach formulated within the 2007 European Floods Directive)—it is no longer believed that there is such a thing as complete protection against floods, but that the damage and loss it inflicts can only be mitigated, and since floods cannot be completely eradicated, societies must learn how to live with them. In the event of a flood, preprepared procedures to counteract and mitigate the effects of the disaster are followed, including the evacuation of people and movable property from affected areas. Evacuation planning is meant to reduce the number of disaster-related (including flood) fatalities and material losses. Crucially, this type of planning requires a well-defined, optimum evacuation policy for people and households within flood hazard areas. In addition, evacuation modelling is particularly important for authorities, planners, and other experts managing the process of evacuation, as it allows for more effective relocation of evacuees to safety. Modelling can also facilitate the identification of bottlenecks within the transportation system prior to the occurrence of a disaster; that is, it enables us to determine the impact of flood-related road closures, and to comprehend—among other things—the effects a phased evacuation has on traffic load. Furthermore, not only may the ability to model alternative evacuation scenarios lead us to establish appropriate policies, evacuation strategies, and contingency plans, but it might also facilitate better communication and information flow. Evacuation from flood-hazard areas is a major challenge for the field of flood risk management as well as the fields of traffic engineering and transport planning. This is particularly true when the research has to include not only those journeys directly related to escape from hazardous places, but also their reflexive relationship with the total number of journeys made in the “background” of the evacuation itself.

Article

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.

Article

On a global scale, natural disasters continue to inflict a heavy toll on communities and to pose challenges that either persist or amplify in complexity and scale. There is a need for flexible and adaptive solutions that can bridge collaborative efforts among public agencies, private and nonprofit organizations, and communities. The ability to explore and analyze spatial data, solve problems, visualize, and communicate outcomes to support the collaborative efforts and decision-making processes of a broad range of stakeholders is critical in natural hazards and disaster management. The adoption of geospatial technologies has long been at the core of natural hazards risk assessment, linking existing technologies in GIS (geographic information system) with spatial analytical techniques and modeling. Practice and research have shown that though risk-reduction strategies and the mobilization of disaster-response resources depend on integrating governance into the process of building disaster resilience, the implementation of such strategies is best informed by accurate spatial data acquisition, fast processing, analysis, and integration with other informational resources. In recent years, new and accessible sources and types of data have greatly enhanced the ability of practitioners and researchers to develop approaches that support rapid and efficient disaster response, including forecasting, early warning systems, and damage assessments. Innovations in geospatial technologies, including remote sensing, real-time Web applications, and distributed Web-based GIS services, feature platforms for systematizing and sharing data, maps, applications, and analytics. Distributed GIS offers enormous opportunities to strengthen collaboration and improve communication and efficiency by enabling agencies and end users to connect and interact with remotely located information products, apps, and services. Newer developments in geospatial technologies include real-time data management and unmanned aircraft systems (UAS), which help organizations make rapid assessments and facilitate the decision-making process in disasters.

Article

The level of interest in public–private partnerships (P3s) is growing—along with supporting literature—and applications are expanding to include new areas where industry supplements public investments in return for measurable rewards. In what follows are timely observations to support P3 operating principles for natural hazards governance—working as an integrated team, sharing innovations, solving technical and operational problems, and engaging in voluntary associations to creatively solve problems. P3s involve voluntary collaboration to achieve common goals and financial benefit. In a globalized economy with highly interconnected systems, this spirit of innovation, sense of personal responsibility, and vision for collective partnerships can be seen throughout the world in the application of P3s. The impact and efficacy of P3s is not just realized in the pursuit of economic, security, safety, social, and environmental goals, but also in establishing integrated governance policies to contend with the persistent vulnerabilities of natural hazards. The emerging world of P3s and natural hazards governance can be illustrated by three real-world examples: (1) a catastrophic regional natural disaster; (2) an urban research-study focused on the measurement of critical infrastructure resilience; and (3) a summary of transportation systems in the unique environment of maritime ports. From these case studies, and a diverse selection of references, it highlights key findings that will benefit future research, critical analysis, and policy application, including academic value, integrated participation, evidence-based metrics, smart resilience, and future innovation.