Anna Bozza, Domenico Asprone, and Gaetano Manfredi
In the early 21st century, achieving the sustainability of urban environments while coping with increasingly occurring natural disasters is a very ambitious challenge for contemporary communities. In this context, urban resilience is a comprehensive objective that communities can follow to ensure future sustainable cities able to cope with the risks to which they are exposed.
Researchers have developed different definitions of resilience as this concept has been applied to diverse topics and issues in recent decades. Essentially, resilience is defined as the capability of a system to withstand major unexpected events and recover in a functional and efficient manner. When dealing with urban environments, the efficiency of the recovery can be related to multiple aspects, many of which are often hard to control. Mainly it is quantified in terms of the restoration of urban economy, population, and built form (Davoudi et al., 2012). In this article, engineering resilience is defined in relation to cities’ capability to be sustainable in the phase of an extreme event occurrence while reconfiguring their physical configuration. In this view, a city is resilient if it is sustainable in the occurrence of a hazardous event.
Accordingly, in an urban context, a wide range of nonhomogeneous factors and intrinsic dynamics have to be accounted for, which requires a multi-scale approach, from the single building level to the urban and, ultimately, the global environmental scale. As a consequence, cities can be understood as physical systems assessed through engineering metrics. Hence, the physical dimension represents a starting point from which to approach resilience. When shifting the focus from the single structure to the city scale, human behavior is revealed to be a critical factor because social actors behave and make choices every day in an unpredictable and unorganized manner, which affects city functioning. According to the ecosystem theory, urban complexity can be addressed through the ecosystem theory approach, which accounts for interrelations between physical and human components.
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.
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.
Spatial and urban planning are acknowledged as important tools and processes that influence exposure to natural and technical hazards and risk accumulation, as well as risk and vulnerability reduction. Even though natural hazards (such as floods) and technical hazards have been discussed in spatial and urban planning for quite some time in various countries and regions, only in a very few cities and regions has there been a sufficient and systematic approach to establish risk management as part of the planning task within the field of spatial planning and urban land-use planning. Risk management strategies in spatial and urban planning have often been strengthened after major crises, such as severe fires in the middle ages in cities in Europe, or after major floods or hurricanes in North America, Asia, and Latin America, as well as Europe and Africa. In this context, risk management is understood as a cluster of concrete and practical strategies and actions on how to handle risks, and in terms of spatial and urban planning, including those risks that are of spatial importance or significant with regard to planning processes.