Uncertainty analysis in WWTP model applications: a critical discussion using an example from design

Gürkan Sin, Krist Gernaey, Marc B. Neumann, Mark C.M. van Loosdrecht, Willi Gujer

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This study focuses on uncertainty analysis of WWTP models and analyzes the issue of framing and how it affects the interpretation of uncertainty analysis results. As a case study, the prediction of uncertainty involved in model-based design of a wastewater treatment plant is studied. The Monte Carlo procedure is used for uncertainty estimation, for which the input uncertainty is quantified through expert elicitation and the sampling is performed using the Latin hypercube method. Three scenarios from engineering practice are selected to examine the issue of framing: (1) uncertainty due to stoichiometric, biokinetic and influent parameters; (2) uncertainty due to hydraulic behaviour of the plant and mass transfer parameters; (3) uncertainty due to the combination of (1) and (2). The results demonstrate that depending on the way the uncertainty analysis is framed, the estimated uncertainty of design performance criteria differs significantly. The implication for the practical applications of uncertainty analysis in the wastewater industry is profound: (i) as the uncertainty analysis results are specific to the framing used, the results must be interpreted within the context of that framing; and (ii) the framing must be crafted according to the particular purpose of uncertainty analysis/model application. Finally, it needs to be emphasised that uncertainty analysis is no doubt a powerful tool for model-based design among others, however clear guidelines for good uncertainty analysis in wastewater engineering practice are needed.
Original languageEnglish
JournalWater Research
Volume43
Issue number11
Pages (from-to)2894-2906
ISSN0043-1354
DOIs
Publication statusPublished - 2009

Keywords

  • Biokinetic
  • WWTP
  • Uncertainty
  • Hydraulics
  • Activated sludge models (ASM)
  • Influent
  • BSM1
  • Design

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