Canal Controllability Identification Based on Automation Theory to Improve Water Delivery Efficiency in Irrigation Canal Systems
Publication: Journal of Irrigation and Drainage Engineering
Volume 149, Issue 8
Abstract
Canal controllability is an open and significant topic that addresses the unreliability/uncertainty in water delivery, efficiency, and modernization in the irrigation system. The study developed an analysis tool for canal controllability to estimate controllable performance and reduce the uncertainty of water delivery under steady and unsteady flow. We designed a linear quadratic control algorithm and applied it to the Nongchang test canal to verify the tool reliability and improve efficiency of water utilization. Finally, the effects of hydraulic variables on canal controllability were quantified. The numerical model of unsteady flow showed satisfactory predictions of water level (correlation coefficient, root mean square error, and mean absolute percentage error were 0.929%, 0.293%, and 12.86%, respectively). The Nongchang test canal was rather controllable (controllability indicator 0.265 to 0.279), implying that linear quadratic control algorithm was appropriate. The algorithm performed well under all conditions tested; the maximum absolute error was 3.66%–8.65%. The water level remained stable (deviation usually less than 0.05 m) and water delivery met user demands in terms of flow rate (the measure of performance relative to adequacy was 92.51%–98.94%) with relatively small gate movements. The bottom slope and roughness were the principal contributors to controllable performance, explaining approximately 46% of the variance. Specifically, controllability was highest when the bottom slope was low, and the roughness and side slope were high. We offer a reliable and flexible tool for assessment of canal controllability. Study results demonstrated that stakeholders benefit when conventional canal operation is modernized. The work will guide automation and upgrading of canal hardware as irrigation becomes optimized.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors are very grateful to reviewers for providing invaluable suggestions and comments. This study was financially supported by the National Key R&D Program of China (Grant Nos. 2021YFD1900600 and SQ2021YFE011918), the Key Research and Development Program of Ningxia Province (Grant No. 2020BCF01002), and the Qinghai Province Science and Technology Program (2019-SF-A4). This research was also funded by Tsinghua -Ningxia Yinchuan Smart Water Digital Water Control Joint Research Institute (Grant No. SKL-IOW-2019TC1903).
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Published In
Journal of Irrigation and Drainage Engineering
Volume 149 • Issue 8 • August 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Apr 9, 2022
Accepted: Aug 20, 2022
Published online: May 17, 2023
Published in print: Aug 1, 2023
Discussion open until: Oct 17, 2023
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