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Updated: Sep 16, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Addressing data sharing challenges for leakage management in water distribution networks - An MCDM-based assessment
Ruoqing Yin1, Haonan Xu2, Jiaqian Wei3
1Department of Civil, Environmental and Geomatic Engineering, UCL, London, UK.
Abstract:
Around 20 percent of drinking water is lost through leakage in the UK's water distribution system with serious economic, environmental and social consequences. Accurate and timely data are essential for both data-driven and model-based approaches to leakage detection. Key research gaps include the lack of comprehensive identification of data-sharing barriers and solutions, the absence of tailored data standards for leakage management, and the need for a holistic framework to assess benefits and prioritize barriers need to be solved. To address these gaps, this study employs a semi-structured interview approach with 7 experts in the UK water sector to identify key barriers and solutions. Additionally, Multiple-Criteria Decision-Making (MCDM) methods, along with the Criteria Importance Through Intercriteria Correlation (CRITIC) technique, are used to assess the identified barriers and solutions. The contributions of this study include a comprehensive data description of water leakage, the identification of 22 barriers categorized into five groups-legal, collaboration, commercial, cultural, and technical-and 19 solutions classified into six categories-regulatory, collaboration, trust-building, technical, training, and sustainability. Using the CRITIC-MCDM approach, each barrier and solution is assigned a prioritization score. The findings reveal that collaboration, cultural, and technical barriers emerged as the most significant obstacles to data sharing. In contrast, technical, training, and trust-based solutions emerged as the most impactful enablers, with measures like advanced technology adoption and sensitive data protection scoring highest. To ensure effective implementation and mitigate potential risks, we emphasize the need to apply a system thinking approach that considers the interdependencies among these high-impact solutions.
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