Abstract.Various methods are currently used in order to predict shallow landslides within the catchment scale. Among them, physically based models present advantages associated with the physical description of processes by means of mathematical equations. The main objective of this research is the prediction of shallow landslides using TRIGRS model, in a pilot catchment located at Serra do Mar mountain range, São Paulo State, southeastern Brazil. Susceptibility scenarios have been simulated taking into account different mechanical and hydrological values. These scenarios were analysed based on a landslide scars map from the January 1985 event, upon which two indexes were applied: Scars Concentration (SC -ratio between the number of cells with scars, in each class, and the total number of cells with scars within the catchment) and Landslide Potential (LP -ratio between the number of cells with scars, in each class, and the total number of cells in that same class). The results showed a significant agreement between the simulated scenarios and the scar's map. In unstable areas (SF≤1), the SC values exceeded 50% in all scenarios. Based on the results, the use of this model should be considered an important tool for shallow landslide prediction, especially in areas where mechanical and hydrological properties of the materials are not well known.

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O método de mapeamento de perigo de escorregamentos em áreas urbanas mais utilizado atualmente no Brasil é o adotado pelo Ministério das Cidades. Com a finalidade de torná-lo mais sistemático e diminuir o grau de subjetividade na comparação e hierarquização dos setores de perigo, porém sem modificar sua abordagem fundamental, o presente trabalho propõe incorporar na análise o Processo de Análise Hierárquica (AHP). Para validar essa proposta foi realizado um ensaio de aplicação em áreas de risco a escorregamentos no Município de São Sebastião (SP), mapeadas anteriormente pelo Instituto Geológico da Secretaria do Meio Ambiente do Estado de São Paulo (IG/SMA/SP), segundo a abordagem tradicional, ou seja, sem a incorporação sistemática do AHP. Os resultados do mapeamento do IG para uma das áreas (Vila Baiana), exemplificada neste trabalho, foram mais conservadores que aqueles obtidos com a incorporação do método AHP. A sua aplicação diminuiu a subjetividade e evidenciou a facilidade e praticidade na ponderação dos indicadores na classificação do perigo. A análise das opiniões de três especialistas nos julgamentos paritários dos indicadores de perigo a escorregamentos mostrou não haver discrepâncias na classificação do perigo.

Accurate daily rainfall estimation is required in several applications such as in hydrology, hydrometeorology, water resources management, geomorphology, civil protection, and agriculture, among others. CMORPH daily rainfall estimations were integrated with rain gauge measurements in Brazil between 2000 and 2015, in order to reduce daily rainfall estimation errors by means of the statistical objective analysis scheme (SOAS). Early comparisons indicated high discrepancies between daily rain gauge rainfall measurements and respective CMORPH areal rainfall accumulation estimates that tended to be reduced with accumulation time span (e.g., yearly accumulation). Current results show CMORPH systematically underestimates daily rainfall accumulation along the coastal areas. The normalized error variance (NEXERVA) is higher in sparsely gauged areas at Brazilian North and Central-West regions. Monthly areal rainfall averages and standard deviation were obtained for eleven Brazilian watersheds. While an overall negative tendency (3 mm·h−1) was estimated, the Amazon watershed presented a long-term positive tendency. Monthly areal mean precipitation and respective spatial standard deviation closely follow a power-law relationship for data-rich watersheds, i.e., with denser rain gauge networks. Daily SOAS rainfall accumulation was also used to calculate the spatial distribution of frequencies of 3-day rainfall episodes greater than 100 mm. Frequencies greater than 3% were identified downwind of the Peruvian Andes, the Bolivian Amazon Basin, and the La Plata Basin, as well as along the Brazilian coast, where landslides are recurrently triggered by precipitation.

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