Systemic Risks, Security, and Robust Solutions
The research focuses on integrated modeling of food, water, and energy security where security is understood as the ability to fulfill the needs of the society for food, energy, and water under standard requirements with respect to their quality and quantity.
Essentially, the new challenge to be addressed is that underlying threats may be generated not only by exogenous events such as heavy rains and droughts, but also by endogenous human-related factors shaped by the decisions of various agents. Under extreme events and other heterogeneities, the use of mean-values, variances, and covariances, least square analysis is misleading; robust solutions require quantile-based approaches, and integration of ex ante and ex post measures with multi-stage decision making under inherent uncertainty.
The project builds on new spatio-temporal stochastic programming tools allowing the incorporation of:
- Quantile-related non-additive performance functions
- A “leader-follower” type of decision environment
- A network structure of multivariate and multicriteria systemic risk measures
- Adversarial threats
- Cascading extreme events dependent on decisions of agents
- Systemic security requirements
- Robust interlinked long-term anticipative and short-term adaptive decisions
- New simulation-based stochastic optimization methods for systems that are too complex for any standard approach to be possible, and
- Development of new probabilistic up-scaling and down-scaling approaches for interdependent data and decisions sets.
The project coordinates two NMO-IIASA collaborative projects: “Integrated modeling of food, energy and water security management for sustainable social, economic and environmental developments in Ukraine”, and “Integrated analysis and modeling of land use efficiency and security under rapid agricultural transition due to urban-rural dynamics in China.” It also contributes to the EC-funded EnRiMa project on development of a decision-making support system for management of energy efficiency and risk in public buildings.
The project is based on achievements of the Integrated Modeling Project (2006-2010), and therefore overlaps with the Advanced Modeling Analytics for Collaborative Decision Support project.