The lab component makes up nearly half of the course, following the motto:
"Learning by doing."
Throughout the lab, you will conduct at least three key numerical experiments:
- Time Series Analysis – Exploring various data elaborations with various Jupyter Notebooks and a little of Python
- Intensity-Duration-Frequency (IDF) Curves – Estimating rainfall intensity over different time scales with various Jupyter Notebooks and a little of Python, as well
- Infiltration Experiments – Investigating soil absorption dynamics using the WHETGEO system
- Evaporation & Transpiration Experiments – Understanding water loss processes in different conditions using the GEOSPACE ssytem
Resources
🔹[Vimeo Showcase – General Lab Videos]
🔹[OSF Repository – Lab Materials]
📌 Detailed videos and materials for each experiment are listed below.
2025-03-03 Introduction to working with Jupyter and Notebooks
- A little introduction to Jupyter Notebook by Concetta D'Amato (YouTube2020, Data).
- A little of introduction
- Elementary operations
- Vimeo2025
- Vimeo2024 part1
- Vimeo2024 part2
- Reading a CSV file with PANDAS
- The Class Notebook I
- Vimeo2025 part1
- Vimeo2025 part 2
- Pluviometria Paperopoli
- Notebook
- Vimeo2024, Vimeo2023, Vimeo2022, Vimeo2021, YouTubeLive 2019, YouTubeVideo2020
2025-03-10 How to read and plot data
- Reading an Excel File
- The Class Notebook II
- Vimeo2025
- (Vimeo2024, Vimeo 2023)
- Data
- Notebook
- Reading a timeseries of daily rainfall organized in a Table whose rows contains the days and columns different years
- Data (Daily Precipitation od San Martino di Castrozza from 1921 to 1990)
- Notebooks:
- Same thing as above (Vimeo2022)
- Chat GPT use suggestions (Vimeo2024)
- Other ChatGPT suggestions (Vimeo2024)
- Grouping the data by year (Vimeo 2022)
- A better plot of the time series
- Monthly mean precipitation (Vimeo2022)
2025-03-25 San Martino Reprise
- Same data as above but with some modified notebooks
2025-03-31 Gumbel derivation
Interpolating the Gumbel distribution to annual precipitation maxima
- with using the mean and the variance (Notebook, Vimeo2025, Vimeo2024, Vimeo2023)
- with the maximum likelihood (Notebook, Vimeo2025 I, Vimeo2025 II, Vimeo2024, Vimeo2023)
- with the minimum square methods (Notebook, Vimeo2025 ,Vimeo2024, Vimeo2023)
- Il test di Pearson (Notebook, Vimeo2025, Vimeo2024, Vimeo 2023)
- Finally interpolating the curves (Notebook, Vimeo2025, Vimeo2024, Vimeo2023)
2025-04-08 Where to find the data
- Finding the data for the Time Series Analysis (Vimeo2025)
2025-05-05 - Installations
- Installing the GEOframe_vincennes environment
- Installing the Java Development toolkit V11
2025-05-06
Below, you'll discover the resources for the second part of the lab, which encompass instructions for utilizing Object Modelling System version 3 (OMS3) models such as WHETGEO1D and GEOET. Within the OMS Projects, you'll find a directory named Jupyter_Notebook, housing sets of notebooks designed to guide you through handling both input and output data for these programs.
A general introduction to some OMS3 concepts
- A Short introduction to OMS3 (Vimeo2025, Vimeo2024)
- The Working Environment (Vimeo2025, Vimeo2024)
- The Simulation File (Vimeo2025, Vimeo2024)
2025-05-11
Introduction to Infiltration with WHETGEO 1D
- Material
- Additional material (oms.py and Runner_ex0_example.ipynb)
- Creation of the WHETGEO - 1D Grid (Vimeo2024)
- Introduction to WHETGEO - 1D (Vimeo2024)
- Ways to visualize the output (Vimeo2024)
- Summary of the instructions (Vimeo2024)
- Time Series Formatter (Vimeo2024)
- How to run the simulation (Vimeo2024)
- Only for the brave: Tubini and Rigon, GMD 2022
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