TY - JOUR
T1 - Physically-based and distributed approach to analyze rainfall-triggered landslides atwatershed scale
AU - Arnone, Elisa
AU - Noto, Leonardo
AU - Lepore, null
AU - Bras, Rafael L.
PY - 2011
Y1 - 2011
N2 - Landslides are a serious threat to life and property throughout the world. The causes of landslides are various since multiple dynamic processes are involved in driving slope failures. One of these causes is prolonged rainfall, which affects slope stability in different ways. Water infiltrating in a hillslope may cause a rise of the piezometric surface, which, in turn, involves an increase of the pore water pressure and a decrease of the soil shear resistance. For this reason, knowledge of spatio-temporal dynamics of soil water content, infiltration processes and groundwater dynamics, is of considerable importance in the understanding and prediction of landslides dynamics.In this paper a spatially distributed and physically based approach is presented, which embeds a slope failure method in a hydrological model. The hydrological model here used is the tRIBS model (Triangulated Irregular Network Real-Time Integrated Basin Simulator) that allows simulation of most of spatial-temporal hydrologic processes (infiltration, evapotranspiration, groundwater dynamics and soil moisture conditions) that can influence landsliding. Slope stability is assessed by implementing the infinite slope model in tRIBS. The model, based on geotechnical and geomorphological characteristics, classifies each computational cell as unconditionally stable or conditionally stable. Soil moisture conditions resulting from precipitation can trigger landslides at conditionally stable locations. When a landslide occurs, the model also computes the amount of detached soil and its possible path downslope.Model performance has been initially tested on a small catchment with very steep slopes, located in the northern part of Sicily (Italy), after a sensitivity analysis concerning some model parameters.
AB - Landslides are a serious threat to life and property throughout the world. The causes of landslides are various since multiple dynamic processes are involved in driving slope failures. One of these causes is prolonged rainfall, which affects slope stability in different ways. Water infiltrating in a hillslope may cause a rise of the piezometric surface, which, in turn, involves an increase of the pore water pressure and a decrease of the soil shear resistance. For this reason, knowledge of spatio-temporal dynamics of soil water content, infiltration processes and groundwater dynamics, is of considerable importance in the understanding and prediction of landslides dynamics.In this paper a spatially distributed and physically based approach is presented, which embeds a slope failure method in a hydrological model. The hydrological model here used is the tRIBS model (Triangulated Irregular Network Real-Time Integrated Basin Simulator) that allows simulation of most of spatial-temporal hydrologic processes (infiltration, evapotranspiration, groundwater dynamics and soil moisture conditions) that can influence landsliding. Slope stability is assessed by implementing the infinite slope model in tRIBS. The model, based on geotechnical and geomorphological characteristics, classifies each computational cell as unconditionally stable or conditionally stable. Soil moisture conditions resulting from precipitation can trigger landslides at conditionally stable locations. When a landslide occurs, the model also computes the amount of detached soil and its possible path downslope.Model performance has been initially tested on a small catchment with very steep slopes, located in the northern part of Sicily (Italy), after a sensitivity analysis concerning some model parameters.
KW - Factor of safety
KW - Hydrological processes
KW - Landslide
KW - Stability
KW - Factor of safety
KW - Hydrological processes
KW - Landslide
KW - Stability
UR - http://hdl.handle.net/10447/59766
UR - http://www.sciencedirect.com/science/article/pii/S0169555X11002637
M3 - Article
VL - 133
SP - 121
EP - 131
JO - Geomorphology
JF - Geomorphology
SN - 0169-555X
ER -