Abstract. Mountain hazard risk analysis for transport infrastructure is regularly based on deterministic approaches. Standard risk assessment approaches for roads need a variety of variables and data for risk computation, however without considering potential uncertainty in the input data. Consequently, input data needed for risk assessment are normally processed as discrete mean values without scatter or as an individual deterministic value from expert judgement if no statistical data are available. To overcome this gap, we used a probabilistic approach to analyse the effect of input data uncertainty on the results, taking a mountain road in the Eastern European Alps as a case study. The uncertainty of the input data are expressed with potential bandwidths using two different distribution functions. The risk assessment included risk for persons, property risk and risk for non-operational availability exposed to a multi-hazard environment
(torrent processes, snow avalanches and rockfall). The study focuses on the
epistemic uncertainty of the risk terms (exposure situations, vulnerability
factors and monetary values), ignoring potential sources of variation in the
hazard analysis. As a result, reliable quantiles of the calculated probability density distributions attributed to the aggregated road risk due to the impact of multiple mountain hazards were compared to the
deterministic outcome from the standard guidelines on road safety. The
results based on our case study demonstrate that with common deterministic
approaches risk might be underestimated in comparison to a probabilistic
risk modelling setup, mainly due to epistemic uncertainties of the input
data. The study provides added value to further develop standardized road
safety guidelines and may therefore be of particular importance for road
authorities and political decision-makers.