In Partnership with the Fulbright Scholars Fellowship, University of Trento Italy, Portland State University USA, and EURAC Italy
18 – 21 February, 2025 – In-person at University of Trento, Italy, and remotely via Zoom.
Instruction Format: Collaborative teaching with structured lectures (morning) and hands-on exercises or fieldwork (afternoon). Lectures will be recorded and posted for future access.
Instructors: Kelly E. Gleason1, John Mohd Wani2, Giacomo Bertoldi4, Michele Bozzoli2,4, Valentina Premier4, and Riccardo Rigon2,3
The School will be held in person at the Department of Civil, Environmental, and Mechanical Engineering in Trento
- All sessions will be recorded and made available online after the course.
- No registration fee is required.
- Participants are responsible for their own travel and accommodation expenses.
1. Department of Environmental Science and Management, Portland State University, Portland, Oregon, USA
2. Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy
3. C3A - Center Agriculture Food Environment, University of Trento, San Michele all‘Adige, Trento, Italy
4. Institute for Alpine Environment, EURAC Research Bolzano, Italy
Day 1: Introduction to Snow Hydrology and Snow Processes
Morning (9:00-12:30)
Lecture Session: Intro to Snow Hydrology
Instructor: Kelly Gleason (9:00-10:00)
- General snow hydrology: Overview of snow hydrology.
- Snow energy and mass balance: Energy and mass dynamics in snowpacks.
Break: 10:00-10:15
Lecture Session: Spatial and Temporal Distribution of Snow, and how is it changing?
Instructor: Michele Bozzoli (10:30-11:30)
- Snowfall trends in the Alps: Historical and current trends; climate change implications.
Break: 11:30-11:45
Instructor: Kelly Gleason (11:30-12:00)
- Snow-climate-forest interactions: Influence of forests and climate on snow hydrology.
Instructor: Riccardo Rigon (12:00-12:30)
- Permafrost and permafrost/snow relations: Overview of permafrost and its interactions with snow processes and modeling.
Afternoon (14:00-17:00)
- Exercise 1: Snow mass balance calculations (Instructor: Kelly Gleason)
- Students calculate snow energy and mass balance using sample datasets.
- Exercise 2: Snowfall trend analysis (Instructor: Michele Bozzoli)
- Students conduct analysis of real-world snowfall data using statistical tools.
Day 2: Snow Modeling and Data Integration into Snow Modeling
Morning (9:00-12:30)
Lecture Session: Intro to Snow Modeling
Instructor: Kelly Gleason (9:00-10:00)
- General snow modeling: Principles, methodologies, and applications of snow modeling.
- Parameterization of snow processes and integration of empirical data into snow models: Role of observational data in improving model accuracy.
Break 10:00-10:15
Lecture Session: Intro to Snow Modeling with GEOTop
Instructor: John Mohd Wani (10:30-12:30)
- Snow Modeling with the GEOtop Model: Introduction and case study overview.
Lunch 12:30-14:00
Afternoon Lecture
Instructor: Giacomo Bertoldi (14:00-15:00)
o GEOtop Modeling: EURAC research case study in snow modeling
Afternoon 15:00-17:00 (Exercises)
- Exercise 3: Snow model output analysis (Instructor: John Mohd Wani)
- Students use the GEOtop and GEOFrame model output data to evaluate model performance under different conditions relative to snow station data.
Day 3: Remote Sensing and Advanced Applications
Morning 9:00-12:30
Lecture Session: Remote Sensing of Snow
Instructor: Kelly Gleason (9:00-10:00)
· Introduction of Remote Sensing of Snow across Scales: Discussing the principles of detecting snow from field based, drone, airborne, and satellite-based methods.
Break 10:00-10:15
Lecture Session: Remote Sensing of Snow and Snow Modeling Case Study
Instructor: Valentina Premier (10:15-11:15)
· Remote Sensing of Snow: Introduction and research in remote sensing of snow
Break 11:15-11:30
Instructor: Michele Bozzoli (11:30-12:30)
- Integration of Remote Sensing and Snow Modeling in the GEOFrame Model: Applications through the lens of PhD dissertation work.
Lunch 12:30-14:00
Afternoon Lecture
Instructor: Kelly Gleason (14:00-14:30)
o Forest/Snow Case Study: Snow and forest interactions and uncertainty in remote sensing observations
Afternoon 14:30-17:00 (Exercises)
· Exercise 4: Remote sensing data uncertainty across scales (Instructor: Kelly Gleason)
o Students use remote sensing observations to estimate snow properties over space and time, and evaluate uncertainty of remote sensing across scales.
Day 4: Fieldwork and Integration of Snow Hydrology Concepts
All day field trip (9:00-17:00) to measure snow properties including snow depth, SWE, density, and grain size.
Morning (9:00-12:30)
Instructors: Giacomo Bertoldi and Kelly Gleason
- Field Trip Introduction: Overview of field methods and objectives.
- Field Data Collection:
- Snowpack measurement techniques (density, SWE, snow depth, grain size).
- Observations of forest-snow and permafrost-snow interactions.
Lunch (12:30-14:00)
Afternoon (14:00-17:00)
Field Data Analysis and Wrap-Up
- Exercise 5: Field snow data analysis (Instructors: Kelly Gleason)
- Students analyze collected snow hydrology data and apply principles learned throughout the course.
- Wrap-Up Discussion:
- Synthesis of course concepts, student reflections, and Q&A.
Graduate Students will conduct a final project conducting mini snow hydrology research project using existing data and analyzing it to answer a simple research question or learning to apply these concepts into the GEOtop model. This mini research project will be documented in a 4-page short form manuscript for submission to instructors for evaluation in the style of the Geophysical Research Letters journal format.
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Materials and Resources
- Daily readings will be provided to prepare for the next day’s coursework.
- Lecture slides and notes (provided by instructors).
- Datasets for exercises and fieldwork preparation.
- Access to GEOtop and GEOframe modeling tools.
Assessment
- Participation in lectures, exercises, and fieldwork (40%).
- Daily exercises will primarily be completed in class during the afternoons, but any unfinished work will be finished by students as homework (30%)
- Graduate student final project conducting mini snow hydrology research project using existing data and analyzing it to answer a simple research question or learning to apply these concepts into the GEOtop model (30%).
This structure ensures a balance of theoretical learning and practical application, allowing students to immediately apply knowledge from lectures to real-world and simulated contexts.
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