Debris flow

Rapid debris flows are among the most destructive natural hazards in steep mountainous terrains. 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 couple the model STEP-TRAMM with simple estimates of debris flow runout distances and pathways. Landslide locations and volumes provided by the triggering model are used as inputs to simulate debris flow runout distances with empirically-based models. Preliminary results demonstrate the added value of linking shallow landslide triggering models with predictions of debris flow runout pathways for a range of soil states and triggering events, thus providing a more complete hazard assessment picture for debris flow exposure at the catchment scale.

To provide simple estimates of debris flow runout length within the framework of the model STEP-TRAMM, we implement the empirical relationship proposed by Rickenmann (1999) linking landslide volume V, elevation difference H between mass release and deposition and runout length L:

                           L = 1.9V0.16H0.83                                                                  

 

Enlarged view: df
Section of the inventory from ‘Prättigau’ 2005 (location is specified by the black box in the inset close to Austria) with observed outflow of the debris flow (brownish area) and 100 simulated runout distances. The colors ranging from yellow to red indicate the number of simulated debris flow paths passing a certain position of the map, highlighting in red the regions where many simulated debris flows are passing (interpreted as paths with high hazard levels).

An even simpler empirical model was postulated by Rickenmann (1999) as L=15V1/3 with debris flow length in meters and landslide volume in cubic meters. In the figure below the performance of the empirical models are compared with two simple physically based models for two landslide inventories (for inventories, see http://www.step.ethz.ch/research/active-projects/landslide-triggering/landslide-model/landslide-inventory.html).

Enlarged view: dfro
Comparison of simulated and measured runout distances for the two landslide inventories ‘Prättigau’ (a) and ‘Napf’ (b) expressed by the cumulative distribution function CDF. The physically-based approaches were fitted with the first inventory (Prättigau). The same parameters were then applied for predicting runout distances for the ‘Napf’ catchment and the results were in good agreement with the observations. Also the predictions based on the empirical approaches with debris flow runout length as function of volume and height (bold black line) match the inventory data, while the simple power-law with L=15V1/3 (dotted black line) deviates from measured values.

By coupling the triggering model with simple empirical relationships between landslide volume and debris flow runout length. It is possible to compare statistics of measured landslides and debris flows with simulated landslides and runout lengths.

Enlarged view: dflic
Comparison of landslide inventory data of Napf 2005 (dashed red line) with six predictions using the STEP-TRAMM model (landslide initiation differing with soil type and soil reinforcement). (a) The landslide volumes predicted by the model are slightly larger than the inventory data (red dashed line) reported by Rickli (2008). The green (sandy loam, cohesion 5 kPa) and blue lines (loam, no cohesion) highlight CHLT-simulations with minimum and maximum volumes, respectively, and the four black lines indicate results for four other CHLT simulations. (b) The predictions of debris flow runout distances for landslides computed with the triggering model overestimate the runout distance but captures the range of measured distances.

To assess the risk (damage) related to a triggered landslide with more sophisticated model approaches, the user-friendly and state of the art model RAMMS (external page http://ramms.slf.ch/ramms/) could be applied.

JavaScript has been disabled in your browser