Effective disaster risk management in a given area relies on the analysis of all relevant risks potentially affecting it. A proper multi-risk evaluation requires the ranking of analyzed risks and the estimation of overall expected impacts, considering possible hazards (and vulnerabilities) interactions as well. Due to their complex and challenging modelling, such interactions are usually neglected, and the analysis of risks derived from different sources are commonly performed through independent analysis. However, often the assessment procedures adopted for the analysis as well as the metrics used to express various risks are different, making results of single risk analyses hardly comparable. To overcome this issue, an approach that allows for comparing and ranking risks is presented in this study. The approach is demonstrated through an application for an Italian region. Earthquakes and floods are the investigated hazards. First, in order to select the case study area, the municipalities within the Veneto region where both risks could be highest are identified by adopting an index-based approach. Then, the harmonization of seismic and flood risk assessment procedure is performed. Sub-municipal areas are selected as scale of analysis and direct economic losses are chosen as common impact metrics. The results of the single risk analyses are compared using risk curves as standardization tool. The EAL (expected annual losses) are estimated through risk curves and the ratios between EAL due to floods and earthquakes are mapped, showing in which area risk is significantly higher than the other.

Identification of risks and vulnerabilities in urban and rural areas is crucial for supporting local authorities in disaster risk reduction and climate change adaptation. Moreover, comparison of risk assessments across different areas may help effective allocation of adaptation funding towards more resilient and sustainable communities. The distinct physical, social, economic, and environmental characteristics of a settlement, along with the relevance of impending hazards, determine the level of risk and vulnerability faced by its residents. While the results of risk assessments will vary from one settlement to another, using general settlement typologies (e.g. coastal cities, dryland cities, and inland or high-altitude cities) can effectively support the understanding of risk in relation to its key drivers, helping to segmentate the complexity in an otherwise too broad problem (Dickson et al., 2012). This study aims to reduce complexity in risk assessment of urban/rural settlements at regional and national scale, ensure a baseline for comparison and identify potential hotspots in risk assessment frameworks. We propose a clustering methodology that groups human settlements based on open-source data, used as proxies of urban vulnerability and exposure. Applying two widely used clustering techniques, we define 18 urban and rural archetypes for the Italian territory, incorporating geographic, demographic, and socio-economic characteristics. These archetypes satisfy multiple validity dimensions of archetype analysis (Piemontese et al., 2022) and can serve as a valuable tool for policymakers. By providing a structured understanding of human settlements vulnerability profiles, they support the design of targeted interventions and resilience strategies tailored to specific risk conditions.