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Fuzzy logic based decision support system for mass evacuation of cities prone to coastal or river flood
|Titre||Fuzzy logic based decision support system for mass evacuation of cities prone to coastal or river flood|
|Type de publication||Thesis|
|Mots clés||Decision support, Flooding, fuzzy logic, Geographic Information System|
|Année de publication||2013|
|University||Université de Technologie de Compiègne|
The increasing risk of river flooding or coastal submersion is already visible through recent events like the storm Xynthia and the floods in the Var department, which caused several dozens of deaths in France. These catastrophic events, even if their extent remains relatively limited, would have justified a preventive evacuation of high risk prone areas. However, the consequences for the population would be much more serious when large cities of hundreds of thousands of people will be partially or totally threatened by floods. This possibility is already an actual danger for large megacities like Bangkok and Alexandria, and also threatens French cities like Tours, Paris or Nice. Being more and more aware of this possibility, big coastal, estuarine and river cities in France, in Europe and in all continents are incited to prepare emergency and mass evacuation plans in order to prevent and cope with exceptional events. The elaboration of these plans is extremely complex and difficult due to technical, organizational, sociological and even political aspects. The great majority of cities in the world prone to large scale disasters do not already have this kind of plan at their disposal. Moreover, the existing state of the art shows that there are few operational tools to help territorial managers implement these plans in the phases of preparation and crisis management. Our work aims to contribute to the development of a support method for the evacuation decision taken in a crisis management context. This method is partly based on the information included in the provisional evacuation plans produced in the preparation phase. To reach this objective, we propose to adapt the tools of the fuzzy logic approach and apply them to a set of synthesized indicators. These indicators or decision criteria have been first selected from a method of evacuation planning previously developed by the research team Avenues-GSU. These criteria integrate classic data on the hazard level (overall forecast level and local flood water levels), the vulnerability of the territory and population and, which is more innovative, some information about the ability of the organization to evacuate and the security or the risk of the evacuation itself. The final result of this method, applied to the spatial dimension with the Matlab and ArcGIS software, is a map of the necessity to evacuate. This map shows the areas with the highest priority to be evacuated according to a fuzzy multicriteria analysis. It has been tested 5 at the pilot site of the city of Bordeaux located upstream in the Gironde estuary, and the theoretical results were compared with historical floods of 1981 and 1999. A hypothetic flood scenario was also studied taking into account the potential climate change impact and the consequences of a 1 meter sea level rise during the 21st century. This method and prototype tool should help policymakers to better understand a complex situation in pre-alert phase and assess the real need for urban zones evacuation on the basis of a limited but representative set of criteria. The maps of the necessity to evacuate represents an innovative proposal which extend and complement the existing official maps of flood forecasting (vigicrue) and its implications in terms of local impacts and crisis management anticipation.