Matthew Bartos, Branko Kerkez

Faced with growing water infrastructure challenges, many cities are now seeking to build digital twins of urban stormwater systems that combine sensor data with online models in order to better understand and control system dynamics. Towards this goal, this study presents pipedream—an end-to-end software toolkit for real-time modeling and state estimation in urban stormwater networks. The toolkit combines (i) a new hydrodynamic solver based on the full one-dimensional Saint-Venant equations and (ii) an implicit Kalman filtering methodology that efficiently updates system states based on observed data. Drawing on sensor data from a real-world stormwater network, we find that the state estimation toolkit is effective at both interpolating system states and forecasting future states based on current measurements. By providing a complete, real-time view of stormwater system dynamics, this toolkit will enable better evaluation of system performance, improved detection of hazards, and more robust implementation of real-time control.