Let’s get the basics. Name, where you are from, and your current affiliation, advisor and profile?

My name is Vangelis Findanis, and I come from Greece, specifically from the Island of Lesvos. I have resided in Thessaloniki for the last 15 years, from the beginning of my undergraduate studies to my seventh year as a PhD student. Currently, I am pursuing a PhD in the Department of Rural and Surveying Engineering at the Aristotle University of Thessaloniki. My advisor is Professor Athanasios Loukas.
What is the research you are currently working on?
My research focuses on applying concepts of information theory to surface hydrology to quantify the uncertainty components of rainfall-runoff models. Information theory originally came from the field of electrical engineering, and it studies the quantification, transmission, and encoding of information. Applications of information theory are everywhere around us, from Morse code to ZIP files and podcasts. To put it simply, without it, our technological world would be infeasible. A key concept of information theory is Shannon’s entropy, which is linked to thermodynamic entropy, implying that information is as physical as energy and mass. Therefore, in a hydrological model, a balance of information must be conserved between its inputs and its outputs, just like the volume of precipitation minus the hydrological losses must be equal to the volume of runoff. Any deficit in that balance is derived by uncertainties entangled in the model’s structure or selected parameters. Hence, by computing this information deficit, the components of uncertainty in a hydrological simulation can be identified and improved.


