Modelo preditivo de suscetibilidade a escorregamentos planares no rebordo do planalto, entre Santa Maria e Candelária - RS, utilizando o método do valor informativo

• Autor(a) principal: Silva, Guilherme Cardoso da
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/001300000hmf0
• Texto Completo: http://repositorio.ufsm.br/handle/1/21213
• topic: Movimento de massa; Escorregamento planar; Técnica do valor informativo; SIG; Rebordo do planalto; Mass movement; Translational landslide; Information value method; GIS; Edge of the plateau; CNPQ::CIENCIAS HUMANAS::GEOGRAFIA

Mass movements are movements that occur along a slope involving the displacement of materials (soil and/or rocks), by gravity, with or without water. In the central region of Rio Grande do Sul, in the region geomorphologically known as “edge of the Plateau”, the mass movements such as translational landslides and debris flows are common. Thus, the objective of this research is to elaborate a susceptibility predictive model of translational landslides to the edge of the Plateau between the municipalities of Santa Maria and Candelária, RS, using the Information Value method. For this purpose, an inventory of translational landslides was prepared, initially identifying scars in satellite images and later confirming in the fieldwork, totaling 61 movements. ALOS PALSAR images were also used to produce a series of thematic maps (hypsometry, slope, aspect, plan and profile curvature, flow direction and TWI), besides data provided by IBGE and CPRM (for geomorphology, geology and soil maps), in order to generate a model that best predicted translational landslides in the study area. For the elaboration of the models, the Informative Value method was used. It was found, from sensitivity tests, that the slope has great influence on the translational landslides of the study area, followed by the TWI (Topographic Wetness Index), geomorphology and hipsometry. Four test models were elaborated, with different combinations of themes, and it was noticed that a combination with a larger number of variables returned better results (success rate and prediction). The final model (model 4) used the following variables: slope, geomorphology, TWI, hypsometry, flow direction, aspect and soil, resulting in a 95% success rate and 92% prediction. The model was divided into five susceptibility classes, and with the estimation group (used in the construction of the model), the two most susceptible classes were able to predict 90.9% of translational landslides, and with the validation group, 79.2%. Thus, it is clear that the Informative Value method was very effective for predicting translational landslide mass movements in the Rio Grande do Sul Plateau, whereas there was a great importance of carrying out the inventory, beyond the field trips. It was also noticed that despite the best result with the largest number of variables, this improvement was not so expressive, demonstrating that sometimes fewer themes can return almost as effective as using a larger group.