Integrative Approach to Multi-Hazard Risk Management for Linear Infrastructure

Linear infrastructure is considered a strategic asset and its interaction with various processes should be viewed from a multi-hazard perspective when conducting risk assessments. To achieve accurate results, various information related to individual hazards must be integrated. In addition to this, vulnerability and exposure of the infrastructure should be evaluated. This research constitutes a part of the SGAM (Smart Geotechnical Asset Management) business application, led by NHAZCA and funded by the European Space Agency (ESA). This project utilises data algorithms and satellite technology for supporting linear asset management and predictive maintenance. Its main objectives are to enhance asset stability and mitigate geological and environmental hazards. It integrates various data sources, including geohazard databases and Earth Observation data, on a platform that partially automates risk assessment for linear assets of stakeholders' interest. A methodology has been developed to research and utilize available data for specific regions. The initial stage involves automating data collection, enabling the method to be applied in any spatial context. The subsequent stage involves refining the data to enhance its precision. Finally, the data is spatially categorised utilizing both physiographic and administrative borders to define regions where there is data homogeneity. The A15 CISA motorway has been chosen as the first pilot area for multi-hazard analysis. The motorway extends over 110 kilometres and passes through the Liguria, Tuscany, and Emilia-Romagna regions, crossing different morphological environments. In the region, there are two distinct Basin District Authorities (Po and Northern Apennine) and three main drainage basins (Ligurian, Magra, and Taro). As a result, there are variations in the data sources in terms of information and spatial coverage. A comprehensive investigation was conducted, examining both regional and national portals. Emphasis was given to geological and hydrogeological statistics, geotechnical factors, land cover specifics, meteorological observations, and hazard maps/inventories associated with geological events. It is essential to evaluate the accuracy of the data and determine what kind of information can be extracted from these sources. An innovative aspect of the research is the creation of a semi-automatic decision-making framework, designed to select the optimal analysis technique based on objective criteria related to the quantity and quality of previously collected data. The selection criteria are linked to the data's scale, accuracy, and key parameters. To provide essential information for management to infrastructure managers, the tool aims to develop and test a methodology in various contexts. In summary, the research represents an innovative approach to managing multi-hazard risks associated with linear infrastructure. Through systematic data organisation and advanced analysis, it aims to facilitate informed decision making for infrastructure managers and to adapt the methodology to different scenarios of data availability.