Reconstructing recent activity of Pyrenean landslides by means of dendrogeomorphological techniques

Corominas, Jordi; Moya, José Luis Barrio; Masachs, I; Baeza, C.; Hürlimann, Martin D.

doi:10.1201/b16816-51

Cited by 1 publication

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some of them evaluated the role played by conditioning factors and triggering mechanisms in different environments and scales (e.g. Pachauri and Pant, 1992;Corominas et al, 2004;Hong et al, 2005). Other studies analysed the influence of external factors such as deforestation (e.g.…”

Section: Introductionmentioning

confidence: 99%

Shallow landslide prediction in the Serra do Mar, São Paulo, Brazil

Vieira¹,

Fernandes

Filho³

2010

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%