Continental Scale Heterogeneous Channel Flow Routing Strategy for Operational Forecasting Models

• Published in: Journal of the American Water Resources Association Vol. 57; no. 2; pp. 209 - 221
• Main Authors: Meselhe, Ehab, Lamjiri, Maryam A., Flint, Kelly, Matus, Sean, White, Eric D., Mandli, Kyle
• Format: Journal Article
• Language: English
• Published: Middleburg Blackwell Publishing Ltd 01.04.2021
• Subjects: Approximation; Backwater effect; Backwaters; Channel flow; Computer applications; diffusive; Disaster management; Disasters; dynamic; Environmental effects; Flood forecasting; Forecasting; Inertia; kinematic; Mathematical analysis; Mathematical models; Model accuracy; National Water Model (NWM); operational; Performance measurement; Routing; Water management; Weather
• ISSN: 1093-474X; 1752-1688
• DOI: 10.1111/1752-1688.12847

The benefits of operational forecasting models to the general public are numerous. They support water management decisions, provide the opportunity to mitigate the impacts of weather‐ and flood‐related disasters and potentially save lives and properties. Channel flow routing is a key component of these models and affects their ability to forecast flood depth, duration, and extent. Continental scale channel flow routing within the operational forecasting environments encounters a broad spectrum of hydraulic characteristics. Deploying computationally demanding approaches, such as the dynamic wave, should be limited in time and space to conditions where the inertia terms are significant (typically in low‐gradient environments and whenever backwater effects are prominent); otherwise, efficient and robust methods, e.g., Kinematic, Muskingum‐Cunge or diffusive waves should be the default. The heterogeneous routing approach presented here provides a framework to evaluate the balance between friction, inertia, and pressure and strategically triggers the appropriate wave approximation. The strategy recommended here is to activate the appropriate wave approximation based on the ambient hydraulic conditions, and smoothly transitions among these approximations. This strategy, if successfully implemented, would strike a balance among the performance metrics of operational forecasting models, namely, computational efficiency, accuracy, and minimization of computational instabilities. Research Impact Statement: A heterogeneous routing strategy, driven by the surrounding hydraulic conditions, activates terms in the momentum equation as needed to strike a balance between computational speed and accuracy.