Water quality parameter estimation for water distribution systems

M. F.K. Pasha, K. Lansey

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Wall decay coefficients vary between pipes and must be determined indirectly from field measured concentration data. A general calibration model for identifying these parameters is formulated here. The problem is solved using the shuffled frog leaping algorithm optimisation algorithm that is coupled with hydraulic and water quality simulation models using the EPANET Toolkit. The methodology is applied to two application networks to examine the robustness of the parameter estimation algorithm and to study the effects of the network flow conditions, data availability, model simplification, and measurement errors. To that end, different field conditions are considered, including a network with or without tanks, altering disinfectant injection policies, changing measurement locations, and varying the number of wall decay coefficients. Results from conditions with exact data show that the solution approach is robust and consistently finds the true parameter values. However, when the number of decay coefficients is increased, results suggest that the distribution and number of meter locations affects model parameter identifiability. It is also noted that the parameter sensitivity is relatively small and related to the velocities in the network. Finally, isolated tracer data can supplement information from normal operating conditions to improve decay coefficient calibration but, if sufficient data is available, the incremental improvement may not be significant. To confirm this result, model calibration must be extended to parameter and model prediction uncertainty.

Original languageEnglish (US)
Pages (from-to)231-248
Number of pages18
JournalCivil Engineering and Environmental Systems
Issue number3
StatePublished - 2009


  • Calibration
  • Parameter estimation
  • Wall decay
  • Water distribution
  • Water quality model

ASJC Scopus subject areas

  • Civil and Structural Engineering


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