Supported by Pillar 1, Pillar 2 aims to provide high-level expertise in mathematics and engineering to assist risk science researchers in developing a more comprehensive approach and in addressing decision-makers’ needs to consider integrated operational variables, criteria, and indicators capable of responding to climatic constraints and socio-environmental changes.
Data exploration for risk assessment, and the design of relevant quantitative measures of risks and decision-support algorithms, remain a challenge as they involve dealing with multifactorial and interdependent phenomena (including human behavior) and numerous, heterogeneous datasets, in a dynamic way across different spatial and temporal scales, while accounting for potentially strong non-stationarities.
This pillar is dedicated to the design of innovative algorithms to provide new quantitative models for Pillar 1 and for the other pillars (3, 4, and 5) of the IRiMa Risks Research Program.
Challenges
- Challenge 1. Manage data quality (heterogeneous, complex data) and model reduction through an interdisciplinary approach combining applied mathematics, digital sciences and technologies, engineering, quantitative social sciences, and environmental sciences.
- Challenge 2. Improve multi-scale and multi-physics modeling, including social and economic issues, specifically adapted to the wide range of spatial scales, (from local to global) and temporal scales (from past to future, taking into account global systemic change), as well as cascading effects.
- Challenge 3. Measure multidimensional risk for decision-making support by better considering interdependencies between infrastructures, cascading effects, and concurrent events in risk assessment methodologies. This entails addressing the full chain from data to model to expert assessment to decision-making.
