Estimating Leakages in Water Distribution Networks Based Only on Inlet Flow Data
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 6
Abstract
The estimate of current real losses in water distribution networks (WDN) is crucial to plan investments for rehabilitation, assess the rise of leakage over time, and possibly drive procedures for failure identification and repair. However, many WDNs worldwide do not have flow/pressure monitoring within the system yet, and the inlet water volume or flowrate is the only recorded data. Developing reliable procedures to estimate real losses in such circumstances is essential to assess the leakage phenomenon and eventually drive the upgrade of existing monitoring systems. This work proposes a simple bottom-up methodology to estimate leakage using WDN inflow data series while only exploiting the seasonal fluctuation of water consumptions. It resorts to a data-assimilation strategy whose formulation is consistent with the physical behavior of WDNs and requires the estimate of only a few numerical parameters. Additionally, the methodology allows the estimation of the user’s daily and night water consumptions, thus being useful to verify or integrate other leakage estimate methods. The methodology is discussed and demonstrated on both synthetic and real WDNs.
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Acknowledgments
This research was supported by the Development and Cohesion Fund 2007–2013—APQ Research Apulia Region “Regional program in support of smart specialization and social and environmental sustainability—FutureInResearch” (Italy) and partly funded by two projects of the National Relevant Scientific Research Program PRIN-2012 (Italy): “Analysis tools for management of water losses in urban aqueducts” and “Tools and procedures for advanced and sustainable management of water distribution networks.”
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 143 • Issue 6 • June 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: May 30, 2016
Accepted: Nov 2, 2016
Published online: Feb 17, 2017
Published in print: Jun 1, 2017
Discussion open until: Jul 17, 2017
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