Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization

Abstract

[1] Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.Citation: von Ruette, J., P. Lehmann, and D. Or (2013), Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization, Water Resour. Res., 49,[6266][6267][6268][6269][6270][6271][6272][6273][6274][6275][6276][6277][6278][6279][6280][6281][6282][6283][6284][6285]

Monitoring and prediction in early warning systems for rapid mass movements

“…New landslide triggering models based on a concept of self-organized criticality were developed to simulate abrupt mass release as progressive failure of soils discretized as interconnected soil columns (Lehmann and Or, 2012;Von Ruette et al, 2013). Such models reproduced the concept that during intense rainfall events, "weak" soil (or snow) units and connections can break and a rapid chain reaction culminating in mass release may be initiated.…”

Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources

“…[17]. Various studies have shown that landslide risk models are able to produce hazard risk maps from mechanical and physical variables [13,[18][19][20].…”

“…Although the key elements of landslide prediction are ground models such as DEMs, other environmental variables such as soil depth, rainfall intensity, and topographic index can increase the validity of the analytical process. Most of these are now publicly available [20].…”

Linking rainfall-induced landslides with predictions of debris flow runout distances

“…Prediction of their path and impact hinges on knowledge of initiation location and the size and constitution of the released mass. To better link mass release initiation with debris flow paths and runout lengths, we propose to capitalize on a newly developed model for rainfallinduced landslide initiation ("Catchment-scale Hydro-mechanical Landslide Triggering" CHLT model, von Ruette et al 2013) and couple it with simple estimates of debris flow runout distances and pathways. Landslide locations and volumes provided by the CHLT model are used as inputs to simulate debris flow runout distances with two empirical-and two physically-based models.…”