Suchergebnisse

IntroductionData indicate an increase in the number of natural disasters in Brazil, with a large share of these events occurring in the state of Minas Gerais. This study examines precipitation-related natural disasters recorded between 1991 and 2016 in Minas Gerais by identifying municipality profiles (encompassing the number of droughts, flash floods, and flooding events), their sensitivity to geophysical and extreme climatic exposure, and their relation to sociodemographic and infrastructure characteristics.MethodsWe combine climate data on seven extreme rainfall indices with elevation data for each municipal seat. We obtained data on droughts, flash floods, and floods from the Center for Engineering and Civil Defense Research and Studies. Population and socio-sanitary characteristics were obtained from the 2010 Brazilian Demographic Census. First, we modeled the climatic-geo-socio-sanitary data using latent class analysis as a pure latent cluster model (LCM) without covariates on seven extreme precipitation indices coupled with altitude data. Subsequently, the LCM was used to identify precipitation-related disaster clusters, including clusters from the 1S-LCM as an active covariate (2S-LCM). Finally, we utilized sociodemographic and infrastructure variables simultaneously with the clusters from the 2S-LCM on an LCM without active covariates (3S-LCM).ResultsOur results show an increase in precipitation-related disasters in Minas Gerais, with municipalities located in the northern part of the state being particularly affected. The state registered 5,553 natural disasters in this period, with precipitation-related disasters representing 94.5% of all natural disasters. The 1S-LCM identified four homoclimatic zones, encompassing a low-altitude dry zone, a relatively low-altitude intermediately wet zone, a relatively high-altitude intermediately wet zone, and a high-altitude wet zone. The 2S-LCM produced four precipitation-related disaster classes, denominated low risk, high risk of excess precipitation, intermediate risk of precipitation deficit and excess, and high risk of precipitation deficit.DiscussionCities with better infrastructure and sociodemographic profiles in semi-arid regions are more resilient to droughts. In richer areas, floods are still a concern where incomplete urbanization transitions may undermine resilience to these events as they increase in intensity with the advance of climate change.

AbstractThe occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model's estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.