Elaboração de mapa de susceptibilidade ao risco geotécnico no Maciço da Tijuca com utilização de modelo probabilístico

• Autor(a) principal: Albuquerque, Simone Nascimento de
• Data de Publicação: 2019
• Outros Autores: [e-mail]
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UERJ
• Texto Completo: http://www.bdtd.uerj.br/handle/1/17792
• topic: Civil engineering; Geotechnical engineering; Bayesian theory of statistical decision; Soil mechanics; Engenharia civil; Engenharia geotécnica; Teoria bayesiana de decisão estatística; Mecânica do solo; ENGENHARIAS::ENGENHARIA CIVIL::GEOTECNICA

The landslides are very common in Rio de Janeiro, especially in summer, where weather conditions are influenced by heat and high humidity, contributing to the formation of areas of instability causing heavy rain. In the city of Rio de Janeiro the Tijuca Massif, Pedra Branca Massif and Gericinó-Mendanha Massif constitute the compartment of coastal massifs, the Tijuca Massif occupies the central position of the municipality. This massif is made up of a wide variety of mountain ranges and hills, some with slopes to the North Zone, others to the city center, others towards the Atlantic Ocean and others to the Jacarepaguá. In some regions of the Tijuca Massif, due to morphology, geological features, urbanization and high population density many mass movements occur that are aggravated mainly in days of heavy rain. In this context it is necessary to have prior knowledge of where the most affected areas, mitigation measures to be employed, and many tragedies don't happen again. In this work, geotechnical risk susceptibility maps were generated using the Bayesian probability update model, from the analysis of reports of geotechnical occurrences in the period of 2010 to 2015 and applying the methodology proposed by Lima (2017), where all occurrences are classified according to with the gravity of mass movement associated with the corresponding susceptibility risk. Probability values defined in each point group, modeling of maps is possible, using the geostatistical interpolation tool of ArcGIS software.