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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Water Management and Conservation Research » Research » Publications at this Location » Publication #170241
Title: AUTOMATIC DOWNSTREAM WATER-LEVEL FEEDBACK CONTROL OF BRANCHING CANAL NETWORKS: SIMULATION RESULTS

Author
item WAHLIN, BRIAN - WEST CONSULTANTS, AZ
item Clemmens, Albert

Submitted to: Journal of Irrigation and Drainage Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/24/2005
Publication Date: 6/1/2006
Citation: Wahlin, B.T., Clemmens, A.J. 2006. Automatic downstream water-level feedback control of branching canal networks: application. Journal of Irrigation and Drainage Engineering. 132(3):208-219

Interpretive Summary: Improving the management of large water distribution networks requires improving the control of water. Controlling the entire network instead of just one portion of the canal system gives operators more opportunity to conserve water. In a companion paper, a methodology was developed to automatically control entire branching canal networks. In this paper, the methodology was applied to a large portion of the canal system operated by the Salt River Project. This canal system consisted of thirty-one pools on three different canals and one river segment. Two existing control algorithms applied to automatically control this large branching canal network. Both algorithms were able to effectively control the system. These results will be of use to the Bureau of Reclamation, irrigation districts, and consultants.

Technical Abstract: Previous research on canal automation has dealt with the control of single, in-line canals, while canal operators typically have to control a network of canals. Because the branches in a network are hydraulically coupled with each other, control of a branching canal network based on separate controllers for each branch may not be the most effective control strategy. A methodology by which existing automatic control systems could be modified to control branching canal networks is provided in a companion paper. This paper uses that methodology to automatically control a large portion of the branching canal system operated by the Salt River Project (SRP) through hydraulic simulation. Two types of controllers were used for this study: Linear Quadratic Regulator (LQR) and Model Predictive Control (MPC). Both controllers used the same underlying process model (Integrator-Delay or ID model). Under feedback control, both controllers gave similar performance. For the LQR controller, we used the volume compensation (VC) method for routing known demand change (feedforward control). For the MPC controller, the ID model was used to route known demand changes. Slight differences were noted in the performance of these feedforward controllers. When feedforward control was included, both of these feedback controllers were able to effectively control the branching canal network operated by SRP.