Riverine floods are one of the most common natural disasters and affect millions of people every year. In this talk, we will explore how deep learning has vastly improved our ability to predict streamflow, the core variable in hydrologic modeling. We will start with a brief introduction to the problem, and then cover the journey from initial research to scientific studies to the full-grown system that now powers Google's operational flood forecasts.