Desastres hidrológicos e vulnerabilidade no Brasil: uma interpretação de estimativas em uma perspectiva demográfica

Abstract

The context of accelerated climate change triggers an increase in the frequency of various extreme climatological events. When these events are associated with conditions of vulnerability, they result in the materialization of disasters. Therefore, knowledge about at-risk populations is of crucial importance for minimizing damage. The dissertation's proposal is to evaluate the utility and application of demographic methods in interpreting hydrological disaster data in Brazil. This analysis is based on data from the Integrated System of Information on Disasters (S2iD), referring to hydrological disasters between 2013 and 2021, and on the population in risk areas in the country, obtained from the Statistical Territorial Base of Risk Areas (BATER). The first objective is to develop rates of those affected by hydrological disasters for the country's geographical macro-regions, taking into account the population mapped by BATER as the population affected by disasters. A significant dispersion in rates is identified, with the Northern region being the area with the highest incidence of those affected during the period, with a rate of 25 per 100 residents at risk, while the Southeast presents the lowest rate, with 0.75. The second objective is to evaluate the application and use of rates in a reduced locality establishing a relationship with the local vulnerability profile. The chosen area for analysis is the Metropolitan Region of Belo Horizonte (RMBH). For this objective, a comparison of rates of those affected by hydrological disasters is made using two different denominators, the population mapped in BATER and the total municipal population. It is observed that rates using the total population denominator showed limitations, only highlighting localities with a high number of those affected. On the other hand, the use of the BATER denominator emphasizes localities with a high proportion of those affected relative to the population in risk areas. Vulnerability indicators in the RMBH show worse economic and sanitary conditions in households exposed to risk, and municipalities with high rates of those affected also showed greater vulnerability. Both for the macro-regions and for the RMBH, the profile of the population at risk reveals a predominance of young people and a lower proportion of elderly people compared to municipal totals. The results indicate good coverage of data on population exposed to risk and point to the applicability of using demographic rates to understand the impact of disasters in the country. There are possibilities for future research agendas based on the data presented, with the prospect of exploring different databases and projections for this population, using other territorial divisions, and evaluating different demographic profiles that emerge from these populations.