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The vulnerability studies of human infrastructure in high-mountain areas influenced by geomorphological hazards in a changing climate are a rather young research field. Especially in high-alpine regions vulnerability maps are often not available, particularly regarding hiking trails or climbing routes. In this paper we present a heuristic approach to create vulnerability maps for Alpine trails and routes in the Grossglockner-Pasterze area (47 degrees 05'N, 12 degrees 42'E), an high-mountain area ranging from about 2000-3798 m a.s.l.. Therefore, the hazard potential that arises from gravitational mass-movements (rock falls, debris falls, other denudative processes) has been modelled in a two step approach. In the first step, the potential source areas were detected using a Digital Elevation Model combined with different further sources of information such as a geological map and orthophotos. Based on the estimation of the volume of the mobilizable substrate - which largely depends on the active layer thickness of permafrost - the second step was carried out by calculating transport paths and dispersal of the downward-moving material. The process model is based on a mass-conserving multiple direction flow propagation algorithm. Both disposition and process model were set up for the current environmental conditions (2010) and for a future scenario (2030) that is driven by a moderate regional climate scenario. Based on the assessment of these processes, susceptibility maps were generated. In a final step, vulnerability maps were created by combining the susceptibility maps with the alpine infrastructure. Considering the length of the trails, 5.5 % are classified in higher hazard classes in 2030 compared to 2010. The presented maps display all known major vulnerable trail and route sections in the study area properly. Furthermore, the evaluation of the maps by local and regional authority experts showed satisfactory results. However, future adaptions of both models - disposition as well as process model - are desirable, especially by the inclusion of better input data based on more empirical information on the processes.

来源平台：AUSTRIAN JOURNAL OF EARTH SCIENCES