Parameter Estimation for Flow in Open-Channel Networks

Abstract

Two mathematical models for parameter estimation in closed-loop, open-channel flow networks are presented. The parameter estimation models seek to determine the parameter values that would reproduce an observed flow profile in the channel network. The governing equations for gradually varied flow in channel networks are the optimization models’ constraints. The projected augmented Lagrangian method is used to solve the optimization models. Performance of these two optimization models is evaluated for a given closed-loop network configuration. Results establish the potential of the developed models for use in real-life flow scenarios.