Abstract
RISKADAPT will provide, in close cooperation with the end-users/other stakeholders, a novel, integrated, modular, interoperable, public and free, customizable user-friendly platform (PRISKADAPT), to support systemic, risk-informed decisions regarding adaptation to CC induced compound events at the asset level, focusing on the structural system. PRISKADAPT will explicitly model dependencies between infrastructures, which, inter alia, will provide a better understanding of the nexus between climate hazards and social vulnerabilities and resilience. Moreover, this project will identify gaps in data and propose ways to overcome them and advance the state of the art of asset level modelling through advanced climate science to predict CC forcing on the structure of interest, structural analyses, customized to the specific structure of interest, that consider all major CC induced load effects in tandem with material deterioration, novel probabilistic environmental life cycle assessment (LCA) and life cycle cost (LCC) of structural adaptation measures and a new model to assess climate risk that will combine technical risk assessment with assessment of social risks. PRISKADAPT will provide values to a set of indicators for each asset of interest, quantifying primary parameters and impacts, in the form of a Model Information System (MIS) that will provide all required information for adaptation decisions. PRISKADAPT will be implemented in the case studies in the pilots that involve specific assets, however, it will permit customization with local values of parameters and data, so it can be applicable throughout Europe for CC adaptation decisions involving assets of similar function, exposed to multiple climate hazards.
Project details
Unibo Team Leader: Silvana Di Sabatino
Unibo involved Department/s:
Dipartimento di Fisica e Astronomia "Augusto Righi"
Coordinator:
Risa Sicherheitsanalysen Gmbh(Germany)
Other Participants:
ALMA MATER STUDIORUM - Università di Bologna
(Italy)
Total Eu Contribution: Euro (EUR) 2.533.536,00
Project Duration in months: 36
Start Date:
01/01/2023
End Date:
31/12/2025
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101093939