Analisi e Gestione dei Sistemi Ambientali

The course (in Italian) develops knowledge and skills for modeling and managing natural systems, and their use to support decision-making. Topics include: decision-making processes, descriptive models (both deterministic and stochastic), and design of management policies. Water resources are used to demonstrate the methodologies presented in the class.

Natural Resources Management

The course develops knowledge and skills for the advanced modelling, management, and control of natural resources systems. The emphasis will be on the operational and real time control aspects of natural resources modeling and management, with a focus on water resources systems and extensive reference to real world case studies. Topics include: natural resources systems modeling for management (from stochastic processes, through linear models, to non-linear model and machine learning), predictive modelling, uncertainty and sensitivity analysis, model diagnostics, stochastic and robust optimal control, approximate control methods (e.g. simulation-based approaches, approximate dynamic programming, reinforcement learning), real time control, and complexity reduction methods. The course is organized into two modules: the 1st module (Prof. Giuliani) develops topics from data to well validated models, the 2nd (Prof. Castelletti) covers algorithms and methods to design optimal decisions and negotiation support systems. The course is aimed at graduate students preparing to work in environmental and water resources engineering field.

Advanced Environmental Systems Analysis - mod. 2

The course offers a systematic overview of policy analysis and 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. The course is aimed at graduate students preparing to work in the environmental engineering field.