Temporal evolution of landslide hazard for a road infrastructure in the Municipality of Nocera Inferiore, Italy, under the effect of climate change

Abstract. In recent years, landslide events have extensively affected pyroclastic covers of the Campania Region in southern Italy, causing victims and conspicuous economic damages. Due to the high criticality of the area, a proper assessment of future variations in landslide occurrences and related risk is crucial for policy-makers, administrators and infrastructure stakeholders. This paper addresses work performed within the FP7 INTACT project, having the goal to provide a risk framework for critical infrastructure while accounting for climate change. The study is a part of the testing and application of the framework in the Campania region, assessing the temporal variation in landslide hazard specifically for a section of the Autostrada A3 Salerno–Napoli motorway, which runs across the toe of the Monte Albino relief in the Municipality of Nocera Inferiore. In the study, hazard is defined as the yearly probability of a spatial location within a study area to be affected by landslide runout given the occurrence of rainfall-related triggering conditions. Hence, hazard depends both on the likelihood of rainfall-induced landslide triggering within the study area and the likelihood that the specific location will be affected following landslide runout. Landslide triggering probability is calculated through the application of Bayesian theory and relying on local historical rainfall data. Temporal variations in triggering probability due to climate change are estimated from present-day to the year 2100 through the characterization of rainfall patterns and related uncertainties using the EURO-CORDEX Ensemble. Reach probability, defining the probability that a given spatial location is affected by debris flows, is calculated spatially through numerical simulation of landslide runout. The temporal evolution of hazard is investigated specifically in the proximity of the motorway, as to provide a quantitative support for landslide risk analysis.