An Evaluation Method of Urban Smart Water Supply System Supported by Fit-For-Purpose Concept and Association Rule

Nan Zhang, Manuel Sebastian Fiallos-Salguero, Yang Liu, Pei Yu, Soon-Thiam Khu and Jia Wang ()
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Nan Zhang: Tianjin University, School of Environmental Science & Engineering
Manuel Sebastian Fiallos-Salguero: Tianjin University, School of Environmental Science & Engineering
Yang Liu: Tianjin University, School of Environmental Science & Engineering
Pei Yu: Tianjin University, School of Environmental Science & Engineering
Soon-Thiam Khu: Tianjin University, School of Environmental Science & Engineering
Jia Wang: Tianjin University of Technology, Institute of Ocean Energy and Intelligent Construction

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2025, vol. 39, issue 15, No 18, 8223-8247

Abstract: Abstract The smart water concept has emerged as a transformative solution to address the shortcomings of traditional urban water supply systems. However, the smart urban water supply systems (USWSS) are integrally complex and multifaceted, making it challenging for managers to gain a well-rounded view of the system’s current state to facilitate its application and improvement. Existing assessment methods for similar systems have several deficiencies such as insufficient evaluation scope, neglect of stakeholder behavior, and a lack of indicators for system “smartness”. This study introduced the Fit-for-Purpose concept into USWSS evaluation and accordingly proposed a multi-purpose DPSIR evaluation method. In addition to the basic evaluation process, the method also involved an indicator recommendation system based on an improved weighted association rule mining algorithm to reduce the uncertainties of subjective indicators. The proposed framework was applied in ten USWSSs in China to analyze the current status and obstacles of system construction. Meanwhile, the recommendation model was verified using the measured data to infer reasonable subjective indicator status and evaluation result level, which exhibited accuracy rates of up to 93% and 100% respectively under proper minimum support and the certain development scenario. Summarily, the proposed method can provide a comprehensive review and scientifically informed insights for urban water supply managers, contributing to enhancing the effectiveness of USWSSs and thus promoting the management and control of urban water resources.

Keywords: Smart water management; System evaluation; Indicator uncertainty; Data mining (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11269-025-04339-8

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