Integrating field measurements, a geomorphological map and stochastic modelling to estimate the spatially distributed rockfall sediment budget of the Upper Kaunertal, Austrian Central Alps

Abstract

The estimation of catchment-scale rockfall rates relies on the regionalisation of local measurements. Here, we propose a new framework for such a regionalisation by the example of a case study in the Upper Kaunertal, Austrian Central Alps (62.5km2). Measurements of rockfall deposition during 12months onto six collector nets within the study area were combined with published mean annual rates from the literature, and a probability density function was fitted to these data. A numerical model involving a random walk routing scheme and a one-parameter friction model was used to simulate rockfall trajectories, starting from potential rockfall source areas that were delineated from a digital elevation model. Rockfall rates sampled from the fitted probability density function were assigned to these trajectories in order to model the spatial distribution and to estimate the amount of rockfall deposition. By recording all trajectories as edges of a network of raster cells, and by aggregating the latter to landforms (or landform types) as delineated in a geomorphological map of the study area, rockfall sediment flux from sources to different landforms could be quantified. Specifically, the geomorphic coupling of rockfall sources to storage landforms and the glacial and fluvial sediment cascade was investigated using this network model. The total rockfall contribution to the sediment budget of the Upper Kaunertal is estimated at c. 8000Mgyr−1, 16.5% of which is delivered to the glaciers, and hence to the proglacial zone.The network approach is favourable, for example because multiple scenarios (involving different probability density functions) can be calculated on the basis of the same set of trajectories, and because deposits can be back-linked to their respective sources. While the methodological framework constitutes the main aim of our paper, we also discuss how the estimation of the budget can be improved on the basis of spatially distributed production rates.