The course offers a systematic overview of policy analysis and environmental decision-making under global change. The emphasis will be on concepts and tools for modeling human decisions in environmental systems subject to demographic, land-use, energy, and climate change. The course develops knowledge and skills for modeling these changes across different spatial and temporal scales, quantifying their impacts at the local scale, assessing the variety of uncertainties associated to future projections, and developing tools to assist decision makers. Real world examples and numerical applications will be developed.
Detailed topics covered include (see also the detailed syllabus):
- Scenario-based analysis: the top-down approach, from global scenarios to the local scale; demographic projections; climate models and IPCC assessment reports; Integrated Assessment Models (e.g., DICE, WITCH) and SSP scenarios; land-use models (e.g., AQUACROP); downscaling techniques.
- Scenario-neutral analysis: the bottom-up approach, from local vulnerabilities to global scenarios; sensitivity analysis and synthetic generation of external drivers; stress test and scenario discovery; exploration of adaptive capacity.
- Robust decision making: decisions under risk vs decisions under deep uncertainty; robustness analysis; robustness, flexibility, and adaptation pathways.
- Nellin, J.D. (2011). Climate Change and Climate Modeling. Cambridge University Press.
- Ray, P. and C. Brown (2015). Confronting Climate Uncertainty in Water Resources Planning and Project Design. The Decision Tree Framework. World Bank Group.
- Peterson, M. (2017). An introduction to decision theory. Cambridge University Press (second edition).
- Additional material (slides, papers) are provided throughout the course.
Exam: The final grading combines a written exam on the lectures’ topics (max 20 points; 12/20 required to pass the exam) with a report on a project related to the laboratory activities (max 12 points).
Tentative calendar for the 2021-2022 academic year.