About Jurian Beunk

Jurian Beunk is a hydrologist and data scientist at Deltares, with a passion for operational hydrological forecasting, machine learning, and assessing the quality of models and forecasts. He develops models and software that enable hydrological and hydrodynamic extremes to be predicted more accurately and the quality of operational forecasts to be systematically evaluated.

After graduating in Earth Sciences from Utrecht University, where he developed a deep-learning model for seasonal drought forecasting, he further specialised in machine learning, data science, and scientific software development.

Within Rijkswaterstaat’s AIWaM programme, he works as a project leader and core team member on new machine-learning models for a wide range of water systems. He also developed an operational LSTM model for discharge forecasting at Lobith and leads the software development of Veriflow, a software package for assessing the quality of operational models and forecasts.