Advancing Uncertainty Quantification in Predictive Hydraulic Simulations of Sanitary Collection System Flows Using Data Assimilation

Amin Mahdipour, Clean Water Services, OR, USA

ABSTRACT

Clean Water Services (CWS) in Oregon is a pioneering public agency dedicated to safeguarding the Tualatin River Watershed through innovative water management strategies. As part of our ongoing eAorts, we have developed a groundbreaking methodology utilizing data assimilation techniques to reduce uncertainty in near-real-time hydraulic and hydrologic simulations of flow rate in sanitary collection systems.

This work is aimed at advancing our understanding of the system dynamics and further enhancing the eAiciency of our modeling and prediction capabilities. By leveraging our comprehensive real-time flow monitoring data, we've been able to significantly improve our predictions by integrating observed data with model predictions to optimize system parameters dynamically.

Data assimilation techniques serve as the foundation of this approach, enabling the correction of model states by reconciling diAerences between observed and simulated data. This iterative process provides a more reliable understanding of the system's state, reducing uncertainty and improving our capability to manage sanitary systems eAectively and responsively.

Our findings have illustrated a substantial increase in the precision of our hydraulic and hydrologic simulations. This has facilitated proactive decision-making processes, particularly in managing anomalies or responding to unprecedented events in the collection system. By continually refining the parameter estimates, we've ensured a robust simulation framework that allows us to maintain and enhance the operation of the collection system and as a result the region's water quality and watershed health.

These advancements have far-reaching implications, not only for CWS but for the broader water utility management industry. As we continue to refine this approach and improve our collection system's predictive capabilities, we pave the way for more eAective waer utility management strategies at the local, regional, and even global level.


Permanent link: