Rockfall runout modelling for hazard zonation considering macro-topographic dispersion

Abstract

To avoid damage on infrastructure and loss of life, rockfall hazard zonation based on numerical simulation, has become an important tool for land use planning. Due to process-complexity and scale-dependency of input data, rockfall runout modelling is still subject to many uncertainties. Based on the specific geologic conditions (e.g. lithology, fabric, discontinuities, tectonics), detached block sizes at the cliff face vary significantly. Furthermore, released rock masses tend to disintegrate into fragments after the first impact. Depending on size and shape of the detached block and boulder/surface interaction, modelling trajectories of these fragments is a difficult task. A few sophisticated simulation tools are able to consider rebound-effects as well as macro-, and micro-topographic factors controlling lateral dispersion. However, these models require a set of high-precision terrain and vegetation roughness parameters – which are typically not available for large areas. We propose an alternative grid-based approach applicable for runout modelling at regional scale, since today high resolution digital terrain models are available for large areas. Thus, we suggest modelling rockfall propagation by considering macro-topographic lateral dispersion and different boulder sizes even at regional scale. For this purpose we used varying coefficients of friction for different boulder sizes and a rockfall model introducing a stochastic multiple flow algorithm to consider lateral dispersion. The results are evaluated by comparing model results with rockfall deposits derived from field mapping and analysis of orthophotos. Furthermore, the method’s reliability is analyzed in terms of iteration-dependency of the stochastic function. The approach and the model setup have been investigated in a small alpine study area. The results demonstrate that the presented method can contribute to rockfall runout modelling with sufficient accuracy for the generation of indicative hazard maps at regional scale.