Acquisition of advanced knowledge on the following geophysical topics: numerical modelling of geodynamic processes; machine learning for geophysical data processing and modeling; physics and mathematics of fluid dynamics and transport phenomena in geological porous media.
This course is compulsory for students of the 39th cycle.
For scheduling, classrooms and more information see the brochure.
Multicomponent reactive transport models combine fluid dynamic in the subsurface and biochemical reactions. This capability make these tools relevant for several transversal topics including hydrogeology, environmental geochemistry , critical raw materials, circular economy , geoengineering and geophysics. The course entails the construction of a groundwater flow and transport model, to which reactions such as cationic exchange, weathering and microbially-mediated reactions are coupled. Case studies proposed by the students are analyzed and modelled
When: February 23-27
Where: Aula Chiesa – Dept. of Earth Sciences, Via Mangiagalli 34
This course examines the dynamic interactions between the terrestrial biosphere and the atmosphere, with particular focus on the role of turbulence in controlling energy, water, and carbon fluxes across the land surface, especially above forests. Adopting an interdisciplinary perspective that bridges micrometeorology, ecology, and environmental physics, the course aims to build a comprehensive understanding of the physical and biological processes that govern ecosystem–atmosphere exchanges.
The course has the main aim of providing basic knowledge for performing spatial analysis and modeling geospatial data in different fields of Earth Sciences, using different Geographic Information Systems, visual and traditional programming languages. Furthermore, the course will also provide the basis for properly managing both the input and the output research data.
This course offers a practical introduction to R programming, emphasizing its application in data exploration and analysis. Participants will learn the essentials of scripting in R, delve into Exploratory Data Analysis (EDA), and explore multivariate techniques for interpreting complex datasets. The program also covers the basics of time series analysis, spatial data interpretation using interpolation methods, and an introduction to Machine Learning for developing data-driven models. Ideal for beginners and professionals looking to expand their data analysis toolkit.
This course examines the geomorphological effects of mass tourism in mountain regions, focusing on environmental challenges and sustainable management. Topics include ski tourism’s impact, forest roads, erosion, and landscape degradation. Students will explore strategies to reduce human pressure and manage protected areas amid rising tourism demand. Case studies provide insights into sustainable tourism practices.