WARREDOC International Winter School on Data Rich Hydrology 2019

The "Data Rich Hydrology" Winter School 2019 took place in beautiful Colombella, Perugia (Italy). It was jointly organised by the Water Resources Research and Documentation Center (WARREDOC) and UNESCO World Water Assessment Program (WWAP). The WARREDOC was established at the Università per Stranieri di Perugia (UNISTRAPG) since 1985 - developing research, advanced training and scientific communication in the field of water, environment and disaster risk management.

http://warredoc.unistrapg.it/en/events/2019-winter-school/

The days were organised into a serious of lectures and lab sessions and food and accommodation were provided all at the location of the Villa Colombella, that was an extraordinary experience. We were completely immersed in this place students and lecturers altogether.

The program encompassed mainly lectures of absolute high scientific standard and well presented by the experienced and well-known lecturers.

- The Era of Data Rich Hydrology, 1st keynote lecture, by Prof. Rafael L. Bras

Prof. Bras is one of the forefathers of hydrology (Google Scholar). He gave us a history lesson of conceptual, numerical and later computational hydrology and modelling of catchments. He concluded with the outlook of what we as young hydrologists should keep striving towards to improve understanding and modelling of the hydrological cycle.

- The WWDR and SDG 6 Synthesis Report, 2nd keynote lecture, by Prof. Stefan Uhlenbrook, also head of UNESCO WWAP

- Remote sensing and data assimilation in hydrology by Prof. Fabio Castelli

- Hydrologic modelling in a data rich world by Prof. Prof Riccardo Rigon

- Citizen science and big data in hydrology by Prof. Fernando Nardi

- Beyond traditional extreme value theory: lessons learned from rainfall and hurricane intensity by Prof. Marco Marani

More topics got covered by further renowned professors, researchers and practitioners in hydrological and hydraulic modelling:

- Groundwater hydrology and hydrological process mechanics
- The water-food-energy nexus
- Modelling scaling properties of precipitation fields
- Hydrologic measurements and novel observation technologies
- Drones in Hydrology (lecture & hands on)
- Hydrological risk assessment: Return period and probability of failure
- Advances in the space-time analysis of rainfall extremes
- Data poor vs. data rich cases for flood hazard (lecture & hands on)
- Distributed Data quality and urban flood modelling uncertainty
- Stream flow measurements: ground and satellite observations
- Remote sensing data and tools to foster inland water monitoring and flood modeling

I also had the pleasure to get interviewed by research fellow and PhD student Francisco Pena, who does a radio show on Disaster Risk Reduction. We had a great chat about our ideas and views on the topics and lectures during this Winter School on Hydrology and did some brainstorming:

http://www.radiophonica.com/podcast/13941 (link to the radio show)

If you like to check out Francisco's pages: https://www.linkedin.com/in/franciscope%C3%B1a/ (LinkedIn) and and https://twitter.com/FebronioPena (Twitter)

Info Session for MSc programme in Geoinformatics for Urbanised Society

Today we broadcast a webinar info session about the new MSc programme in Geoinformatics for Urbanised Society at the University of Tartu.

One of the recurring core topics in this new MSc curriculum is Data and GIS use in Urban Planning.

Until just a decade ago spatial planning and analytics projects had problems with getting enough data. But nowadays there is so much data available, that it is increasingly hard to make sense of it – because of the 3 V’s of big data - volume, variety, velocity. The open data movement, government agencies, research institutes and citizen scientists alike make more and more data available publicly, mobile phones, sensor networks and satellites generate a multitude of datasets every day

In order solve the Interdisciplinary challenges of urban planning we want to empower you with skills and knowledge to analyse, visualise and understand processes and data. For that we teach the Full cycle of spatial data management, from the various methods of data acquisition, followed by efficient and practical processing techniques, to subsequent meaningful analysis and visualisation; in order to consequently make successful planning decisions for a sustainable future.

So what does it mean to study Geoinformatics for Urbanised Society with us in Tartu?

You will learn how to combine geography and IT in the age of BIG data. This is essentially what we believe modern Geoinformatics is representing. Mastering Geoinformatics will provide you with tools to analyse social and natural processes in space for interdisciplinary decision- and policy-making.

Watch the whole recorded session for more info:

Links:

• https://www.ut.ee/gis 
• https://www.facebook.com/GISTartu

A Python Pandas Coding Meetup

On October, 12th, I organised a local meetup event at the Department of Geography. We had around 15 attendees, both from Tartu industry and university students.

In this meetup we played with the Jupyter Notebook (http://jupyter.org/) and did some data wrangling with Python, Pandas (http://pandas.pydata.org/) and co., some data analysis and visualisation.

I presented on how we can use Miniconda, an encapsulated versatile virtual python environment installer, that works under the hood of the big Anaconda python distribution. Miniconda is basically a mini version of Anaconda that includes only the conda package manager and its dependencies. We used a Python version 3.4 because some of the libraries/tools we wanted to work with supposedly only are supported up to Python 3.4. Here it becomes obvious how practical virtual environments can be. They help you to keep various Python versions around without messing up your system.

After we had set-up our local Python working environment, I introduced the Jupyter Notebook. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

I prepared a variety of resources that we worked through in the meetup. I shared the collated tutorials and course materials on my GitHub account, The repository contains a curated collection of Jupyter Notebooks of introductory materials about programming in Python in general, the Pandas data manipulation and visualisation toolkit, and the Geopandas geospatial library.

This repository aims at different degrees of experience with the Python programming language and Python data manipultation and visualisation libraries. Each folder contains a README.md (for the the online repository) and README.notebook.md (readme as readable Notebook) file that list the contents and some details for each of the 3 big modules here:

• 01 - Introduction to Python and the Jupyter Notebook
• 02 - Introduction to the Pandas library
• 03 - Introduction to the Geopandas library

In order to get started, download the full Meetup-Repositiry from https://github.com/allixender/meetup-notes/archive/master.zip and extract it to a LOCAL folder. Go back into the console/commandline prompt and change into that folder. There you should then start the Jupyter notebook.