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Benefit-Cost Analysis of Economic Resilience Actions  

Adam Rose

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.


Housing Deficit and Disaster Risk Management in Chile  

Natalia Ponce Arancibia

The housing deficit, which affects especially the most vulnerable sectors, corresponds to a constant and growing challenge for housing policies developed in the Chilean context. Its provision presents complexities that respond, to a large extent, to the availability and high values of land as a result of market deregulation. The demand for new housing, in this sense, has been resolved under two mechanisms: through irregular land occupations and self-construction of housing, and through state action and the implementation of programmatic devices for the construction of new residential complexes. Housing developments or settlements are generally located on the margins of urbanized territory—that is, in sectors where land transaction costs are lower due, in part, to possible conditions of risk or territorial vulnerability. These conditions are strongly expressed in the housing configuration and spatial location patterns that characterize the commune of Alto Hospicio, located in the Tarapacá Region in northern Chile. In this commune, whether due to the spontaneous action of the inhabitants or the action of state institutions, housing intended for socially vulnerable sectors is exposed to conditions that can lead to significant losses of residential assets and affect the living conditions of their inhabitants.


Hydrodynamic Modeling of Urban Flood Flows and Disaster Risk Reduction  

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.