Reliability assessment of water distribution systems with statistical entropy and other surrogate measures

Tiku T. Tanyimboh, Marika T. Tietavainen, Salah Saleh

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)
146 Downloads (Pure)


There is ever increasing commercial and regulatory pressure to minimise the cost of water distribution networks even as the demand for them keeps on growing. But cost minimizing is only one of the demands placed on network design. Satisfactory networks are required to operate above a minimum level even if they experience failure of components. Reliable hydraulic performance can be achieved if sufficient redundancy is built in the network. This has given rise to various water distribution system optimization methods including genetic algorithms and other evolutionary computing methods. Evolutionary computing approaches frequently assess the suitability of enormous numbers of potential solutions for which the calculation of accurate reliability measures could be computationally prohibitive. Therefore, surrogate reliability measures are frequently used to ease the computational burden. The aim of this paper is to assess the correlation of surrogate reliability measures in relation to more accurate measures. The surrogate measures studied are statistical entropy, network resilience, resilience index and modified resilience index. The networks were simulated with the prototype software PRAAWDS that produces more realistic results for pressure-deficient water distribution systems. Statistical entropy outperformed resilience index in this study. The results also demonstrate there is a strong correlation between entropy and failure tolerance.
Original languageEnglish
Pages (from-to)437-443
Number of pages8
JournalWater Science and Technology: Water Supply
Issue number4
Publication statusPublished - 2011


  • water distribution systems
  • statistical entropy
  • reliability assessment
  • failure tolerance
  • pressure-deficient water distribution networks
  • pressure-dependent modelling
  • redundancy
  • resilience index


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