HR: 0800h
AN: H51B-0354    [Abstracts]
TI: A Probabilistic Approach to Transient Hydrology and Landslide Triggering
AU: * Simoni, S
EM: silvia.simoni@ing.unitn.it
AF: Department of Civil and Environmental Engineering, University of Trento, via Mesiano 77, Trento, TN 38050 Italy
AU: Rigon, R
EM: riccardo.rigon@ing.unitn.it
AF: Department of Civil and Environmental Engineering, University of Trento, via Mesiano 77, Trento, TN 38050 Italy
AU: Godt, J W
EM: jgodt@usgs.gov
AF: United States Geological Survey, 1711 Illinois, Golden, CO 80401 United States
AU: Savage, W Z
EM: savage@usgs.gov
AF: United States Geological Survey, 1711 Illinois, Golden, CO 80401 United States
AB: We present results from a 3D, transient coupled simulation of hillslope hydrology and slope stability for a steep alpine catchment that experienced shallow landslides during an intense period of rain. These results reproduce observed spatial and temporal distributions of rainfall-induced landslides. The distributed coupled hydrological-geotechnical model, GEOtop-SF, describes processes related to slope hydrology and slope stability. It combines a 3D numerical solution of the Richards equation and a slope-stability analysis. Hydrological processes are simulated by GEOtop which runs on a 3D grid built on detailed topography. It contains a detailed description of the interactions between topography and solar radiation (shortwave and longwave) in order to compute the energy budget and the 3D water balance. The model describes the temporal variation of the water table, of the soil moisture content and of the matric suction within the whole basin. It also simulates the transient pore-water pressure due to infiltration and redistribution processes, which is of primary importance in landslide triggering. The SF module performs the shallow stability analysis by applying a simple infinite-slope model with a probabilistic approach to account for uncertainty of the soil-strength parameters such as soil cohesion, cohesion due to vegetation and internal friction angle. Geotechnical properties are determined through field and laboratory tests. The probabilistic approach reflects the variability and the heterogeneity of the soil that greatly affects local slope stability. Results show that the probability of landsliding varies in space and time. The likelihood of landslide occurrence is greatest a few days after the peak of the precipitation at a depth of 0.8m. At this time the model computes high failure probability for the steepest and unvegetated areas. In addition, the model highlights that, for a given location, this probability increases with depth. Aerial photos of this area show that the model correctly reproduces the location of the main landslides. To assess the capability of the model to reliably reproduce hillslope hydrology leading to landslide triggering in different climatic and topographical conditions we are currently applying GEOtop-SF for typical wet winter conditions for steep coastal bluffs along Puget Sound near Edmonds, WA, using available United States Geological Survey data.
DE: 1871 Surface water quality
SC: Hydrology [H]
MN: Fall Meeting 2005