Pipedream: An interactive digital twin model for natural and urban drainage systems. (October 2021)

• Record Type: Journal Article
• Authors: Bartos, Matthew; Kerkez, Branko
• Is Part Of: Environmental modelling & software. Volume 144(2021)
• Publication Date: 2021-10
• Subjects: Hydraulic modeling -- Data assimilation -- Storm water -- Kalman filtering -- Continuous modeling -- Real-time sensing and control; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.105120
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Faced with persistent flooding and water quality challenges, water managers are now seeking to build digital twins of surface water systems that combine sensor data with online models to better understand and control system dynamics. Towards this goal, this study presents pipedream—an end-to-end simulation engine for real-time modeling and state estimation in natural/urban drainage networks. The engine combines (i) a new hydraulic solver based on the one-dimensional Saint-Venant equations and (ii) a Kalman filtering scheme that efficiently updates hydraulic states based on observed data. Using sensor data from a real-world watershed, we find that the simulation engine is effective at both interpolating hydraulic states and forecasting future states based on current measurements. By providing a complete, real-time view of system hydraulics, our software will enable rapid detection of flooding, improved characterization of maintenance and remediation needs, and robust real-time control for both small-scale (stormwater) and large-scale (river/reservoir) networks. Highlights: We present a digital twin model for stormwater systems that combines a new hydraulic solver with online data assimilation. We show that fusing sensor data into the model improves interpolation and forecasting of stormwater depths and flows. Our model will enable water managers to better detect floods, leaks, blockages, and other emergencies in near real-time.