This paper attempts to provide a decision support framework that can help risk managers in urban areas to improve their decision-making processes related to sustainable management. Currently, risk management strategies should no longer be selected based primarily on economic and technical insight. Managers must address the sustainability of risk management by assessing the impacts of their decisions on the sustainable development of a given territory. These assessments require tools that allow ex ante comparisons of the effectiveness and the likely economic, social and ecological impacts of the alternative management strategies. Therefore, this paper reports a methodological and operational framework, which aims to incorporate sustainability principles in a particular decision by taking all the dimensions that affect sustainability into account. This paper is divided into two main parts: one on the theoretical aspects of the proposed methodology and the other on its application to a flood risks management case in a municipality located in Meurthe-et-Moselle county (France). The results of the case study have shown how the methodology can be suitable for determining the most sustainable decision.

Generating well-informed and reliable predictions for disaster evacuation is a large challenge. Crisis and disaster management policymakers have to deal with poor data quality, a limited understanding of households’ behaviour dynamics, and uncertainty regarding the effects of the various actions/measures in place. Agent-based simulation models are frequently used to support decisions when planning disaster evacuation procedures. However, one of the most important aspects of this issue, which is social influence, is not often considered. Most of existing evacuation models largely overlook the importance of the households’ behaviours and social influences, which leads to oversimplified models. Moreover, it is almost impossible to find models in the literature that focus on the extrinsic decision-making factors of some evacuees, such as compromised lifelines, in the case of catastrophic events. In contrast to the existing evacuation models, this paper suggests a probabilistic agent-based model that relies on theloss of different lifelines as factors affecting evacuees’ decision-making in addition to some intrinsic factors that are used to characterise the propensity of households to evacuate and explicitly allow for social contagion as well as uncertainties to be considered. This model, in which all the variables are considered uncertain and Monte Carlo Simulations are run to estimate the confidence range of the predictions, is tailored to estimate the potential number of inhabitants that have not been evacuated in high-rise buildings in the face of critical infrastructure failures induced by a slow-onset flood and/or the actions taken during the related crisis, considering different uncertainties that may affect the reliability of the prediction. The model has been specifically designed to predict the dynamics of households’ self-evacuations in fourteen residential high-rise buildings located in a flood-prone area in Paris. This paper describes the suggested model and also reports the results of an illustrative case study in which three scenarios are simulated to demonstrate the applicability of the model, to test its effectiveness and to explore the uncertainty regarding some modelling assumptions using sensitivity analysis.

This paper attempts to provide a decision support framework that can help risk managers in urban areas improve their decision-making processes related to sustainable management. Currently, risk management strategies should no longer be selected based primarily on economic and technical insight. Managers must address the sustainability of risk management by assessing the impacts of their decisions on the sustainable development of a given territory. These assessments require tools that allow ex ante comparisons of the effectiveness and the likely economic, social and ecological impacts of the alternative management strategies. Therefore, a methodological and operational framework was drafted and tested using a theoretical case study to illustrate its use, determine the most sustainable decision and identify its improvement trails.

This article presents the results of a prospective survey of households living in the only high rise residential buildings of Paris, which are located in a flood zone. It questions the behavior of households likely to be subject to evacuation instructions in the event of a progressive flooding impacting the functioning of the technical networks and associated urban services. The survey received 523 responses from 11 residential high-rise buildings located in the 15th district of Paris. It assessed the propensity of households to evacuate autonomously through three main factors: the capacity to self-evacuate, to self-host and to go to this temporary accommodation. The survey answers explicit requests for information by local authorities on inhabitants' capacities to self-evacuate and to self-host in order to support the formers' estimation of shelter requirements. The typology of evacuation capacities reveals that most of the respondents are partially dependent due to difficulties relating to re-accommodation issues. Furthermore, many people seems to have an incorrect perception of the public authorities' responsibilities. Information and warning systems could thus be improved, notably through a participative method.