In the construction industry, especially in tunneling or large-scale earthworks projects, huge quantities of excavation material are generated as a by-product. Although at first glance such material is undesirable, in many cases this material, if suitably treated and processed, can be recycled and reused on the construction site and does not necessarily need to be removed and deposited as waste at a landfill. In the simplest case, the material can be used as filling material with the least demanding requirements with regard to rock quality. Material of better quality often can be recycled as aggregate and be used as a substitute for conventional mineral aggregates. This approach generates numerous benefits regarding the costs for material procurement, storage and transport. In addition, reduction in environmental impact and demand for landfill volume can be achieved. The challenge lies in the fact that excavation material is not a standard aggregate in terms of geometric, physical and chemical characteristics and is subject to quality deviations during tunnel driving, mainly depending on the varying geology and applied excavation method. Therefore, preliminary research and experimental testing as well as specific evaluation and continuous examination of the rock quality during tunnel driving is necessary as well as ongoing adjustment of the rock processing plant to finally accomplish a high-quality level of recycled aggregates. This article illustrates the material investigations and treatment processes for the specific example of the Brenner Base Tunnel, the longest underground railway line in the world that is currently under construction. There, material recycling has already been successfully implemented.

Even after decades of intensive research, assessing rock slope stability remains a challenge. One reason for this is the spatial variability of rock bridges (RBs) related to non-persistent, pre-existing geological structures, especially as the detection of RBs is generally limited to the post-failure period. Thus, the identification and classification of RBs and their inclusion in numerical studies are demanding, yet essential, since even small quantities of RBs can be decisive for rock slope stability. In our study, we demonstrate how brittle RB failure and pre-existing geological structures control the mechanisms of a polyphase rock slope failure. Therefore, we present a case study in the Austrian Alps, where three rock falls with a failure volume of 30,000 m³ occurred in 2019. Based on detailed process reconstructions, high-resolution terrain models, and comprehensive geological and rock mechanical investigations, we derived high-quality input for our distinct element model (DEM). By applying asymmetric Voronoi tessellation in the DEM, we modelled the coalescence of pre-existing geological structures by brittle RB failure. As a result, we identified toppling as the predominant failure mechanism at the study site. Distinctive geological structures decisively affected the failure mechanism. However, the toppling failure was only reproducible by incorporating RBs in the DEM in their pre-failure position. Finally, we found that joint persistence, and consequently the presence of potential RBs, controls which initial rock fall failure mechanism was developed. In conclusion, we state that the initial toppling failure of the Hüttschlag rock falls is controlled by non-persistent geological structures in interplay with RBs.

Rock slope failure is commonly regarded as the most significant phase in the evolution of an unstable rock slope. However, many rock slopes do not fail in a single event but rather in several individual ones. Such polyphase rock slope failures impose a challenge, as their post-failure evolution is hard to predict, and the time interval between the failure events, their magnitude, and running-out distance can differ significantly for each respective event. In this study, we present a unique data-set of high-resolution remote sensing data acquired from a 170 m high, steep to overhanging post-failure rock slope over a 3.5-year survey. By applying ground-based interferometric synthetic aperture radar, unmanned aerial vehicle photogrammetry, and a 3D distance approach on terrestrial laser-scan data, we unravel the post-failure rock slope evolution on the example of the Hüttschlag study site (Salzburg, Austria). Accompanied by meteorological data and supported by a discrete element modelling approach, i.e. the asymmetric Voronoi logic, we (i) prove that the post-failure rock slope remains an active system, even 3.5 years after the latest major rock slope failure event, (ii) outline advantages and limitations of the respective remote sensing techniques, (iii) emphasise the challenge of identifying unambiguous triggers, and link this challenge to progressive failure within a fractured, anisotropic rock mass. Our findings highlight the importance of considering the time-dependency of rock mass strength and improve our understanding of post-failure rock slope evolution and rock mechanical processes in complex geological media.

Natural hazards pose an increasing threat to infrastructures, lives, and livelihoods in alpine regions due to climate change and the growing demand for settlement space. While grey protective structures are commonly deployed to provide immediate safety, their sustainability, and thus protective function, is limited by cost-intensive maintenance. Nature-based solutions (NbS) can alleviate these shortcomings by offering cost-effective, adaptive protection that strengthens over time, making their deployment a key factor in building resilience to climate-induced hazards. This paper introduces a systematic methodology for the strategic deployment of NbS to enhance climate resilience. It integrates a three-level hazard classification system with an expert-led assessment rating 74 NbS against 29 hazards. A subsequent Principal Component Analysis (PCA) synthesises these into six functional groupings based on their shared mitigation characteristics. The core of this framework introduces two key innovations: a novel Mitigation Score and a Hazard Mitigation Profile. Together, they evaluate NbS effectiveness dynamically through the different phases of natural hazards, surpassing traditional static ratings by evaluating NbS performance across the hazard management cycle—from predisposition to post-event recovery. Significant variation in mitigation scoring was observed for individual hazard classes and types. Erosion processes (e.g., sheet, rill, and gully erosion) achieved the highest mitigation scores (1.90), as they can be addressed by many highly effective NbS (21–33 types). Conversely, flood-related hazards, such as fluvial and pluvial floods, showed moderate scores (1.64–1.66) with a balanced mix of mitigative and supportive NbS, while options for mitigating impact floods and coastal floods were far more limited (1.00–1.42). The resulting methodology provides a crucial, practical link between specific climate-related threats and viable, nature-based responses, serving as a robust framework to guide the decisions of planners, engineers, and policymakers. By enabling a more strategic and temporally aware deployment of NbS, our findings inform the development of adaptive management strategies to ensure their long-term effectiveness.

Climate change is increasing the frequency and intensity of natural hazards, placing additional stress on critical infrastructure systems. Addressing these challenges requires both robust evaluation frameworks and the inclusion of Nature-Based Solutions (NbSs) alongside conventional protection measures. Building on the RAMSSHEEP concept, originally proposed for risk-driven maintenance, and later further developed and applied in, e.g., previous Horizon projects and COST Action TU1406, this study integrates natural hazard considerations and NbS risk mitigation measures into a comprehensive approach to evaluate the resilience of critical infrastructure. The novel methodology involves a structured expert elicitation process with participants from the Horizon NATURE-DEMO project, to adapt and extend the RAMSSHEEP framework for resilience-oriented transformation. This also includes alignment with established hazard and risk assessment systems to ensure methodological consistency and applicability of the final concept. The resulting framework enables systematic evaluation of infrastructure vulnerability and resilience, explicitly accounting for natural hazards and the contribution of NbSs to risk mitigation. The expected outcome is an objective, repeatable assessment methodology that supports decision-makers in planning, prioritizing, and monitoring resilience-enhancing measures across the infrastructure life cycle. A particular focus of this contribution lies in the methodological approach, ensuring its applicability within interdisciplinary and multi-level decision-making contexts.