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Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty

Katrijn Cierkens UGent, Salvatore Plano UGent, Lorenzo Benedetti UGent, Stefan Weijers, Jarno de Jonge and Ingmar Nopens UGent (2012) WATER SCIENCE AND TECHNOLOGY. 65(2). p.233-242
abstract
Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH4 predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
confidence interval, calibration data frequency, full-scale modelling, input data frequency, model structure, output uncertainty, WWTP model calibration, ACTIVATED-SLUDGE MODELS
journal title
WATER SCIENCE AND TECHNOLOGY
Water Sci. Technol.
volume
65
issue
2
pages
233 - 242
Web of Science type
Article
Web of Science id
000299324000006
JCR category
WATER RESOURCES
JCR impact factor
1.102 (2012)
JCR rank
44/80 (2012)
JCR quartile
3 (2012)
ISSN
0273-1223
DOI
10.2166/wst.2012.081
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2084501
handle
http://hdl.handle.net/1854/LU-2084501
date created
2012-04-12 09:41:18
date last changed
2012-04-17 10:28:40
@article{2084501,
  abstract     = {Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH4 predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.},
  author       = {Cierkens, Katrijn and Plano, Salvatore and Benedetti, Lorenzo and Weijers, Stefan and de Jonge, Jarno and Nopens, Ingmar},
  issn         = {0273-1223},
  journal      = {WATER SCIENCE AND TECHNOLOGY},
  keyword      = {confidence interval,calibration data frequency,full-scale modelling,input data frequency,model structure,output uncertainty,WWTP model calibration,ACTIVATED-SLUDGE MODELS},
  language     = {eng},
  number       = {2},
  pages        = {233--242},
  title        = {Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty},
  url          = {http://dx.doi.org/10.2166/wst.2012.081},
  volume       = {65},
  year         = {2012},
}

Chicago
Cierkens, Katrijn, Salvatore Plano, Lorenzo Benedetti, Stefan Weijers, Jarno de Jonge, and Ingmar Nopens. 2012. “Impact of Influent Data Frequency and Model Structure on the Quality of WWTP Model Calibration and Uncertainty.” Water Science and Technology 65 (2): 233–242.
APA
Cierkens, K., Plano, S., Benedetti, L., Weijers, S., de Jonge, J., & Nopens, I. (2012). Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty. WATER SCIENCE AND TECHNOLOGY, 65(2), 233–242.
Vancouver
1.
Cierkens K, Plano S, Benedetti L, Weijers S, de Jonge J, Nopens I. Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty. WATER SCIENCE AND TECHNOLOGY. 2012;65(2):233–42.
MLA
Cierkens, Katrijn, Salvatore Plano, Lorenzo Benedetti, et al. “Impact of Influent Data Frequency and Model Structure on the Quality of WWTP Model Calibration and Uncertainty.” WATER SCIENCE AND TECHNOLOGY 65.2 (2012): 233–242. Print.