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.
Federico Marco Federici
Communication underpins all phases of disaster risk reduction: it is at the heart of risk mitigation, by increasing resilience and preparedness, and by interacting with affected communities in the response phase and throughout the reconstruction and recovery after a disaster. Communication does not alter the scope or severity of a disaster triggered by natural hazards, but the extent to which risk reduction strategies impact on affected regions depends greatly on existing differences inherent in the society of these regions. Ethnic minorities and multilingual language groups―which are not always one and the same―may become vulnerable groups when there has been little or no planning or no awareness of the impact of limited access to trustworthy information when the disaster strikes. Furthermore, large-scale disasters are likely to involve personnel from the humanitarian sector from both local and international offices. Communication in most large-scale events has progressively become multilingual; from the late 20th and early 21st centuries, it is expected that large disasters see collaboration between intergovernmental, governmental, local, national, and international entities that operate in different ways in rescue and relief operations. Regardless of linguistic contexts, communication of reliable information in a trustworthy manner is complex to achieve in the aftermath of a disaster, which may instantaneously affect telecommunication infrastructures (overloading VOIP and GPS systems). From coordination to information, clear communication plays a role in any activity intending to reduce risks, damages, morbidity, and mortality. Achieving clear communication in crisis management is a feat in a monolingual context: people from different organizations and with different capacities in multi-agency operations have at least a common language, nonetheless, terminology varies from one organization to another, thus hampering successful communication. Achieving effective and clear communication with multilingual communities, while using one language (or lingua franca), such as English, Arabic, Spanish, or Hindi, depending on the region, is impossible without due consideration to language translation.
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.