Contributed by Maria-Helena Ramos (Irstea) and Shaun Harrigan (CEH)
This year Hepex is joining the Young Hydrologic Society (YHS) to offer a short course on hydrological forecasting during the EGU General Assembly in Vienna.
Shaun Harrigan (CEH), representative of the YHS, and I have been excited about this first experience and invite you to check the short description of the course’s content.
The course will take place on Wednesday 26 April, from 17:30-20:00, in room -2.91 (Brown Level -2 – Basement floor). It will be given by two active members of the Hepex community:
Marie-Amélie Boucher is a professor at the University of Quebec at Chicoutimi (UQAC). She has written several Hepex blog posts as a columnist in 2015 and a general contributor: “In Canada, I teach disciplines such as hydrology, hydraulics and fluid mechanics. My main research interests revolve mostly around ensemble forecasting and include multi-model forecasting, data assimilation, pre and post-processing and assessing the socio-economic value of forecasts.”
Jan Verkade is a researcher in hydrology as well as a developer of flood forecasting systems at Deltares and a flood forecaster for the Rijkswaterstaat River Forecasting Service in the The Netherlands. He is one of the creators of the Hepex Portal in 2013 and since then has been helping to manage it: “My research interests focus on hydrologic forecast, warning and response systems. I have ample experience in the development of operational, real-time hydrological forecasting systems and in applications of research findings in projects around the world. I have also
aged matured grown up greyed considerably since this photo was taken.”
Can you tell us a little about what you are preparing for this course in Vienna?
JV: There will be some focus on the elements that distinguish realtime forecasting from modeling, including realtime data feeds, management of model states and state updating runs, data assimilation, primary and secondary data validation and forecast verification. Also, we will not strictly limit ourselves to “forecasting” and will give some attention to the use of forecasts: communication thereof, use in decision making, etc.
MAB: I won’t reveal too much: people have to come to the course to know its content in greater detail! However, I can tell you that we are tailoring the course to people who already have some background in hydrological modelling. We will assume that participants already know how to set up a model (any model) that runs in continuous mode, for instance, and that they have already done or worked with model simulations. Obviously, those who read the HEPEX blog are probably more than okay with that! So, this course is for anyone with some background in hydrology, and a participant does not need to be a forecaster to join us.
Why should an Early Career Scientist (or even an established researcher or flood forecaster) take the opportunity to attend this course?
JV: Realtime forecasting is a discipline in itself but, despite its obvious relevance to society, receives relatively little attention in university curriculae. Here’s one of very few opportunities to learn more about it!
And one final question: what was your worst experience ever with hydrological forecasting (model, data, real-time forecasting…)?
JV: Over the years I have come across many issues related to pretty much all aspects of realtime forecasting. Many pertain to automated data feeds (precipitation gauges, numerical weather predictions) where something was wrong but, for one reason or another, the issue escaped detection by validation procedures. Biblical floods resulted – on screen, in any case. Others related to physical processes not included in the numerical models: a particular rain-on-snow event springs to mind. Yet others related to the handling of ‘states’. There was always lots of opportunity to learn!
MAB: Well, nothing dramatic, really! I crave the collaboration with operational forecasters and sometimes I hear about some bad experiences from them, but they are not my own! My research is always performed in hindcast mode (I’m a huge fan of the TIGGE data portal, for instance!), which probable makes things easier. Still, I definitively have a “least preferred hydrological model” when running my forecasting experiments. I guess we all have one, depending on personal experiences. From my experience, the implementation of this particular model requires disproportionate efforts considering the quality of the results it gives (compared, for instance, to simpler models). It also has those obscure error messages. I especially dislike the one that simply says that “[model’s name] is going to close now”. But I still have to work with it sometimes (I won’t detail why…), so maybe I’ll eventually learn one day to appreciate it (or to improve it!).
Thank you, Marie-Amélie and Jan, for your answers and your availability to prepare the EGU course!
For those willing to attend the course, you just need to be in Vienna for the EGU and show up in room -2.91 (Brown Level -2 – Basement floor) on Wed 26 April. Attendance will be on the basis of first come, first served!
See you there!