@article{Damasceno_Cardoso_Paiva_2022, title={Investigation of the relationship between rain and landslide in the municipality of Mauá - SP to obtain critical thresholds that trigger landslides}, volume={43}, url={https://periodicos.ufsm.br/cienciaenatura/article/view/43119}, DOI={10.5902/2179460X43119}, abstractNote={The Mauá city, Region of Grande ABC Paulista, is among the five municipalities of the São Paulo state with the most critical situation in relation to the number of records of geological accidents, which makes it vulnerable to intense and persistent rainfall. This study investigates the relationship between precipitation events and landslide occurrence in this municipality from the geological-geotechnical characterization of samples representative of the horizons most susceptible to the region’s geodynamic processes, precipitation patterns and the frequency of landslides. It was found that rains of different intensities and durations can increase the number of landslides. In addition, the geological and geotechnical characteristics of the region’s pedological horizons (residual soil from mica schist and granite) and anthropic interventions contribute to the magnitude of susceptibility to geodynamic and related processes. The curves of landslides obtained, for different criteria of daily and accumulated precipitation before the occurrence, showed that the greater the accumulated value of precipitation, the lower the intensity of daily precipitation necessary to trigger the landslides. The criteria indicated the daily total of 35 mm as the most restrictive, regardless of the value accumulated in days prior to the occurrences, which was validated with the cases of recent landslides occurred in the region, not considered in the calibration of the adjustment equation. In addition, in periods without rain in the previous days, the landslides will tend to occur with rainfall greater than 70 mm on the day of the event, an increase of this value may be observed with the increase in the number of previous dry days.}, journal={Ciência e Natura}, author={Damasceno, Aloa Dandara Oliveira and Cardoso, Andrea de Oliveira and Paiva, Cláudia Francisca Escobar de}, year={2022}, month={Jan.}, pages={e50} }