An innovative methodology for characterizing Coping Capacity (CC), Adaptive Capacity (AC), and Transformative Capacity (TC) resilience determinants in a multi-hazard territorial context is applied to the Soccavo district (Naples, Italy), located in the Campi Flegrei caldera and exposed to volcanic eruptions, ground deformations (bradyseism), earthquakes, geomorphological processes (landslides, rock falls, erosion), and climate change-related hazards (heat waves, pluvial floods). The method allowed for the identification of the CC, AC, and TC parameters that can be easily converted into qualitative–quantitative variables. Among all parameters, the method focused on multi-stakeholder and civil society engagement, which is representative of TC and variable relating to the risk perception and awareness, the urban space perception, or the people’s ability to activate bottom-up urban transformation processes within resilient development pathways. Therefore, qualitative tools such as collaborative mapping and co-design processes, pertaining to the urban planning and design fields, and quantitative tools such as surveys, from the social science field, were harmonized and combined to collect and analyze data on these site-specific topics. Considering people’s priorities and needs, the study was useful to define shared sustainable and resilient solutions in order to holistically integrate Disaster Risk Reduction/Climate Change Adaptation urban planning and design approaches and simultaneously deliver social, environmental, and economic co-benefits.

The re-mobilization of volcaniclastic material poses a hazard factor which, although it decreases with time since the last eruption, remains present in the hydrographic basins of volcanic areas. Herein, we present the results of the numerical modelling of erosive phenomena of volcanic deposits, as well as of flooding in the volcanic area. The proposed approach includes runoff estimation, land use analysis, and the application of hydraulic and erosion modelling. It exploits the Iber software, a widely used and validated model for rainfall-runoff, river flooding, and erosion and sediment transport modelling. The methodology was applied to the Island of Vulcano (Italy), known for the erosion phenomena that affect the slopes of one of its volcanic cones (La Fossa cone). The rainfall excess was calculated using a 19-year dataset of hourly precipitations, and the curve number expressed by the information on soil cover in the area, derived from the land cover and land use analysis. The erosion and flow models were performed considering different rainfall scenarios. Results show a particularly strong erosion, with thicknesses greater than 0.4 m. This is consistent with field observations, in particular with some detailed data collected both after intense events and by long-term observation. Results of the hydraulic simulations show that moderate and torrential rainfall scenarios can lead to flood levels between 0.2 and 0.6 m, which mostly affect the harbours located in the island’s inhabited area.

Volcanic regions are popular tourist destinations thanks to their unique landscapes, rich biodiversity, and natural resources. However, increasing tourist flows heighten exposure to natural hazards, thereby amplifying volcanic risk, as shown by the escalation in eruption-related fatalities and injuries, as well as other types of risks, given that these areas are often subject to multi-hazard conditions. This study investigates risk awareness among the local population and tourists on the island of Stromboli, a permanently inhabited volcano, during the July–August 2019 eruptive crisis, which was marked by two paroxysmal explosions. A mixed-methods approach was employed, combining semi-structured interviews with inhabitants and survey questionnaires targeting tourists. The findings revealed contrasting awareness profiles. Inhabitants displayed more structured, place-based knowledge and a deeper understanding of natural phenomena, related hazards, and their potential impacts, largely shaped by direct experience and consistent public outreach by scientists and civil protection authorities. Conversely, tourists often exhibited a fragmented or superficial awareness, which is likely shaped by informal or non-specialist sources. While the study adopts a multi-hazard perspective, volcanic risk emerged as the dominant concern, with limited awareness of other significant threats, such as earthquakes, landslides and tsunamis, particularly among tourists. The methodological framework proved effective in capturing diverse perspectives and may be applied to other multi-hazard, high-tourism settings. These insights contribute to a more nuanced and integrated approach to disaster risk management in regions characterised by demographic variation and pronounced seasonal fluctuations in exposure.

The risk/impact assessment of climate-related extreme events has been historically addressed through single-hazard approaches that so far limited the development of a comprehensive, harmonized and integrated multi-hazard modelling framework capable of holistically understanding the weight of climate impacts on complex socio-eco-technological systems, as well as the definition of possible climate-resilient development pathways (IPCC, 2022). The expected increase in frequency and magnitude of meteorological hazards aggravated by climate change often manifests itself through the occurrence of complex interactions, characterised by compound events (e.g., floods and landslides, triggered by heavy rainfalls) and cascading effects (e.g., forest fires fuelled by persistent drought, triggered by heat wave conditions).Depending on how the combination of these events occurs over time and space, the impacts resulting from multi-hazard conditions might be greater than the sum of the effects of individual hazards, and the nature of the damage will vary depending on both the complexity and interdependencies between hazards and/or impacts involved. Understanding the implications of compound events (whether coincident or consecutive) on specific categories of risk receptors – and of cascading effects arising from the propagation of impacts across assets and services – is the starting point to develop an asset-level modelling framework that effectively supports and orients decision-making processes towards the identification of strategies and measures to improve resilience.In this perspective, a paradigm shift towards an effective multi-hazard impact modelling approach requires that 1) the possible interactions between hazards, and their dependence on global warming and climate change trends are taken into account, 2) the multi-sectoral consequences of complex impact scenarios leading to cascading effects are identified, and 3) the effect of possible organizational, spatial, functional and physical resilience measures targeting multiple hazards are evaluated.This contribution presents the holistic multi-hazard impact modelling framework developed within the EU-funded Horizon Europe ICARIA Project (Improving ClimAte Resilience of crItical Assets, www.icaria-project.eu, GA: 101093806). The framework aims at ensuring consistency in the analysis across different hazard categories (heat waves, forest fires, droughts, floods, storm surges, and wind gusts, including compound events), a harmonized evaluation of exposure and vulnerability of critical assets (buildings, open spaces and infrastructures) and services (water, transport, energy, waste, natural areas, and tourism sectors) potentially at risk, and the potential tangible direct and indirect impacts of complex multi-hazard scenarios, including cascading effects across interconnected service networks and systems. The modelling framework is also designed to quantify the benefits of resilience strategies and measures and to define suitable, sustainable and cost-effective solutions for climate resilience.The methodological approach is grounded on interconnected “elementary bricks”, namely Hazard, (H) Exposure (E), Vulnerability (V), Dynamic Vulnerability (DV), and Damage (D), framed with respect to time and space interdependencies and interacting with local Coping Capacity (CC), Adaptive Capacity (AC) and Transformative Capacity (TC) as main resilience components. The contribution introduces relevant taxonomies, replicable modelling workflows, and quantifiable impacts and resilience metrics applicable in different geographical contexts, proposing a service-oriented implementation approach aimed at maximising the exploitation of existing models and data while introducing specific methods to address uncertainties and data/knowledge gaps.