Response Surfaces for Water Distribution System Pipe Roughness Calibration
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 3
Abstract
Water distribution system (WDS) model calibration research has focused on estimating model input/output parameters and analyzing several uncertainties (e.g., model uncertainty) to improve models with best-fit parameters. Numerous studies have shown that optimization algorithms generally quickly converge to very good parameter solutions. However, the generality and reasoning behind this have not been identified. This paper examines the shape and convexity of WDS response surfaces (i.e., objective function surfaces) and whether the surfaces have single global or multiple local optima. To that end, three networks with different network topologies are evaluated: (1) the Modena network as presented, (2) a modified form of the Modena network, and (3) a real Austrian network. Various conditions were evaluated to consider field measurement error, parameter uncertainty through pipe grouping, and model uncertainty. Results demonstrate that the response surfaces remained smooth and convex even when uncertainties are introduced, but the best parameter solutions are shifted from the true solution. The impact and sensitivities of the uncertainties are evaluated by examining the change in best-fit parameter estimates.
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Data Availability Statement
All of the data, models, and code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This material is based in part upon the work supported by the National Science Foundation (NSF) under Grant No. 1762862. Any opinions, finding, and conclusions or recommendations expressed in this material are those of author(s) and do not necessarily reflect the views of the NSF.
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Journal of Water Resources Planning and Management
Volume 148 • Issue 3 • March 2022
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© 2021 American Society of Civil Engineers.
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Received: Mar 6, 2021
Accepted: Oct 27, 2021
Published online: Dec 20, 2021
Published in print: Mar 1, 2022
Discussion open until: May 20, 2022
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