Mitigation

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.

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.

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.

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.

Natural disasters pose important problems for societies and governments. Governments are charged with making policies to protect public safety. Large disasters, then, can reveal problems in government policies designed to protect the public from the effects of such disasters. Large disasters can serve as focusing events, a term used to describe large, sudden, rare, and harmful events that gain a lot of attention from the public and from policy makers. Such disasters highlight problems and, as the public policy literature suggests, open windows of opportunity for policy change. However, as a review of United States disaster policy from 1950 through 2015 shows, change in disaster policy is often, but not always, driven by major disasters that act as focusing events. But the accumulation of experience from such disasters can lead to learning, which can be useful if later, even more damaging and attention-grabbing events arise.