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  • Volume 65, Issue 7

An assessment of static and dynamic models to predict water treatment works performance

Roger Swan, John Bridgeman, Mark Sterling
Published November 2016, 65 (7) 515-529; DOI: 10.2166/aqua.2016.005
Roger Swan
Mouchel Consulting, Kier, 2 Parade, Sutton Coldfield B72 1PH, UK E-mail: roger.swan@mouchel.com
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John Bridgeman
School of Civil Engineering, University of Birmingham, Edgbaston B15 2TT, UK
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Mark Sterling
School of Civil Engineering, University of Birmingham, Edgbaston B15 2TT, UK
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Abstract

The relative accuracy of static and dynamic water treatment works (WTWs) models was examined. Case study data from an operational works were used to calibrate and verify these models. It was found that dynamic clarification, filtration and disinfection models were more accurate than static models at predicting the final water quality of an operational site but that the root mean square errors of the models were within 5% of each other for key performance criteria. A range of abstraction rates at which the WTWs was predicted to operate adequately were identified using both types of models for varying raw water qualities. Static clarification, filtration and disinfection models were identified as being more suitable for whole works optimisation than dynamic models based on their relative accuracy, simplicity and computational demands.

  • accuracy
  • dynamic
  • model
  • Monte-Carlo
  • static
  • water treatment works
  • First received 28 January 2016.
  • Accepted in revised form 19 August 2016.
  • © IWA Publishing 2016
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SELECTED ISSUE

Journal of Water Supply: Research and Technology - Aqua: 67 (2)
  Volume 65, Issue 7

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An assessment of static and dynamic models to predict water treatment works performance
Roger Swan, John Bridgeman, Mark Sterling
Journal of Water Supply: Research and Technology - Aqua Nov 2016, 65 (7) 515-529; DOI: 10.2166/aqua.2016.005
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An assessment of static and dynamic models to predict water treatment works performance
Roger Swan, John Bridgeman, Mark Sterling
Journal of Water Supply: Research and Technology - Aqua Nov 2016, 65 (7) 515-529; DOI: 10.2166/aqua.2016.005

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Keywords

accuracy
dynamic
model
Monte-Carlo
static
water treatment works
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