Avaliação dinâmica dos riscos de inundações como ferramenta para auxiliar um planejamento integrado de medidas da gestão destes riscos

Abstract

Urban populations are increasingly exposed to flooding, a situation aggravated by unplanned urban growth, the fragility of existing infrastructure, and the insufficiency of essential services such as sewage and solid waste collection or adequate housing provision. These combined factors intensify the impacts of flood events, heightening risks to the physical integrity, health, and safety of the population, as well as to the functioning of essential sectors. In this context, this dissertation proposes the development of a Socioeconomic Flood Risk Index (IRSI), constructed by combining socioeconomic information of the studied basin with flood mapping, while introducing a dynamic analysis of risk both during the flood event (variation in hazard characteristics) and over time (variation in socioeconomic conditions). A distinctive feature of the proposal is the incorporation of hydrodynamic simulations performed with the MODCEL software, which make it possible not only to identify flood-prone areas and maximum inundation levels, but also to analyze their variations throughout the duration of flood events. This provides a dynamic, spatial, and temporal assessment of flood risks. The test application of the IRSI was carried out in the Acari River Basin, located in the northern zone of Rio de Janeiro, an area characterized by social vulnerability and frequent flooding. The results enabled more detailed interpretations of risk over time and across different areas of the basin, revealing with greater precision the impacts on populations in vulnerable conditions. This refined diagnosis can provide valuable input for the formulation of risk management guidelines, encompassing measures of prevention, mitigation, preparedness, and response, thereby strengthening community resilience to flood events. Furthermore, it highlights aspects of risk associated with the persistence of flooding—an issue often obscured in assessments that focus solely on maximum inundation depths.