A spatiotemporal optimization model for the evacuation of the population exposed to flood hazard

Author:

Alaeddine H.ORCID,Serrhini K.,Maizia M.,Néron E.

Abstract

Abstract. Managing the crisis caused by natural disasters, and especially by floods, requires the development of effective evacuation systems. An effective evacuation system must take into account certain constraints, including those related to traffic network, accessibility, human resources and material equipment (vehicles, collecting points, etc.). The main objective of this work is to provide assistance to technical services and rescue forces in terms of accessibility by offering itineraries relating to rescue and evacuation of people and property. We consider in this paper the evacuation of an urban area of medium size exposed to the hazard of flood. In case of inundation, most people will be evacuated using their own vehicles. Two evacuation types are addressed in this paper: (1) a preventive evacuation based on a flood forecasting system and (2) an evacuation during the disaster based on flooding scenarios. The two study sites on which the developed evacuation model is applied are the Tours valley (Fr, 37), which is protected by a set of dikes (preventive evacuation), and the Gien valley (Fr, 45), which benefits from a low rate of flooding (evacuation before and during the disaster). Our goal is to construct, for each of these two sites, a chronological evacuation plan, i.e., computing for each individual the departure date and the path to reach the assembly point (also called shelter) according to a priority list established for this purpose. The evacuation plan must avoid the congestion on the road network. Here we present a spatiotemporal optimization model (STOM) dedicated to the evacuation of the population exposed to natural disasters and more specifically to flood risk.

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

Reference38 articles.

1. Alaeddine, H., Maïzia, M., Serrhini, K., and Néron, E.: A mezoscopic vehicles pursuit model for managing traffic during a massive evacuation, University of Tours, Tours, France, 2014a.

2. Alaeddine, H., Néron, E., Serrhini, K., and Maïzia, M.: A novel polynomial algorithm for the lexicographic maximum dynamic flow problem with several sources applied to evacuation planning, University of Tours, Tours, France, 2014b.

3. Alaeddine, H., Serrhini, K., Maïzia, M., and Néron, E.: Finding the K-best paths in evacuation network, University of Tours, Tours, France, 2014c.

4. Alaeddine, H., Serrhini, K., Néron, E., and Maïzia, M.: Traffic assignment algorithms for planning a mass vehicular evacuation, University of Tours, Tours, France, 2014d.

5. Ardekani, S., Ghandehari, M., and Nepal, S.: Macroscopic speed-flow models for characterization of freeway and managed lane, The University of Texas, Department of Civil Engineering, Arlington, USA, 2011.

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