These projects are the winners of the 2024 call for proposals, which comprised two priority themes:
Data–models–decision continuum:
The multiplicity of observational data (Earth observation, geophysics, monitoring networks, citizen sensors, and so on) calls for new strategies of processing, analysis, and integration into phenomenological, statistical, or numerical models. The way in which these processing chains are formalised directly influences decision support, particularly in crisis situations: uncertainties, the diversity of spatio-temporal scales, the interdependencies between observables, and the plurality of users are all components that must be mastered in order to guarantee the quality of the maps and indicators employed. Knowledge of risk can be deepened through the exploitation of historical records, through experimental approaches, observational means, or the numerical modelling of the processes involved — from the hazards themselves to the impacts on exposed assets and the social and economic vulnerability of territories. Changes of scale, non-stationary contexts, the quantification of uncertainties, the hybridisation of physically based models with artificial intelligence, and the use of digital twins are among the key questions.
Adaptation to global change:
Climate change and the increasing concentration of exposed assets subject our societies to growing risks, of both climatic and geophysical origin, which must be anticipated using complex exposure scenarios that integrate multiple phenomena, climate trajectories, and socio-economic dynamics, over horizons extending to 2120. These trajectories must inform new proposals for public policy — prevention, sustainable risk reduction, crisis management, and adaptation — in mainland France as well as in the overseas territories, from natural environments to industrial settings. To be operational, such adaptation requires multi-stakeholder strategies (scientists, authorities, private actors, citizens) grounded in information sharing and collective decision-making, in which the risk sciences fully deploy their multidisciplinary and integrative dimension.
