Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

A Risk-Based Multicriteria Approach for Assessing and Monitoring Flood Disasters Under Heavy Precipitation

Lucas Borges Leal da Silva1,3, Maria Clara Fava2, Marcelo Hazin Alencar3, Rodrigo José Pires Ferreira3, Adiel Teixeira de Almeida4 and Danielle Costa Morais4

1Management Engineering Department, Universidade Federal do Rio Grande do Norte - Natal, Rio Grande do Norte, Brazil /EADDRESS/
2Institute of Exact and Technological Sciences (IEP), Universidade Federal de Viçosa - Rio Parnaíba, Minas Gerais, Brazil.

3Research Group on Risk Assessment and Modeling in Environment, Assets, Safety, Operations and Nature (REASON), Universidade Federal de Pernambuco - Recife, Pernambuco, Brazil.

4Center for Decision Systems and Information Development (CDSID), Universidade Federal de Pernambuco - Recife, Pernambuco, Brazil.


Public administration, whether at the local or national level, faces new challenges in adapting human life to alarming trends such as an increase in the extent and frequency of natural disasters, threats to food and water supply, inadequate energy distribution, and migration crises. Given this context, the worsening of the climate crisis forces policymakers to adopt a new perspective to combat its damaging impacts on urban functioning, especially concerning the quality of life under the occurrence of hydrological events. This problem is multifaceted so usually conflicting objectives impose hard dilemmas to decision-makers (DMs) once heavy precipitations can potentially promote fatalities, displacements, contamination of water bodies, economic losses, and others. This paper aims to propose a novel multicriteria decision model for assessing and monitoring flood disasters, using the DM's subjective preferences to establish value judgements under risky situations. A numerical application in a Brazilian municipality is performed with the aid of a Decision Support System (DSS) with views to validate the new approach. By integrating statistical, graphical, and tabular information, this model is replicated in other urban areas in which the model assumptions are assumed. Moreover, the model results can be analyzed by DMs not only for taking preventive actions against floods but also for enhancing early warning systems to reduce disasters.

Keywords: Disaster risk management, Multi-criteria decision-making, Urban flood risk, FITradeoff.

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