A Sequential Pressure-Based Algorithm for Data-Driven Leakage Identification and Model-Based Localization in Water Distribution Networks
Publication: Journal of Water Resources Planning and Management
Volume 148, Issue 6
Abstract
Leakages in water distribution networks (WDNs) are estimated to globally cost and cause water and revenue losses, infrastructure degradation, and other cascading effects. Their impacts can be prevented and mitigated with prompt identification and accurate leak localization. In this work, we propose the leakage identification and localization algorithm (LILA), a pressure-based algorithm for data-driven leakage identification and model-based localization in WDNs. First, LILA identifies potential leakages via semisupervised linear regression of pairwise sensor pressure data and provides the location of their nearest sensors. Second, LILA locates leaky pipes relying on an initial set of candidate pipes and a simulation-based optimization framework with iterative linear and mixed-integer linear programming. LILA is tested on data from the L-Town network devised for the Battle of Leakage Detection and Isolation Methods. Results show that LILA can identify all leakages included in the data set and locate them within a maximum distance of 374 m from their real location. Abrupt leakages are identified immediately or within 2 h, while more time is required to raise alarms on incipient leakages.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in online repositories in accordance with funder data retention policies (Vrachimis et al. 2020b; Daniel et al. 2021; Pesantez 2021). Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to thank the BattLeDIM Committee for organizing and managing the BattLeDIM competition and for coordinating and guest editing this special collection. Moreover, the authors acknowledge the support of HEIBRiDS. JP would like to acknowledge the Government of Ecuador for its funding. This material is based on work that was partially supported by the US National Science Foundation’s Division of Industrial Innovation and Partnerships under Grant PFI-1919228.
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Journal of Water Resources Planning and Management
Volume 148 • Issue 6 • June 2022
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© 2022 American Society of Civil Engineers.
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Received: Apr 25, 2021
Accepted: Dec 10, 2021
Published online: Mar 30, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 30, 2022
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