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Generation of (synthetic) influent data for performing wastewater treatment modelling studies

Flores, Xavier LU ; Ort, Cristoph; Martin, Cristina; Benedetti, Lorenzo; Belia, Evangelina; Snip, Laura; Saagi, Ramesh LU ; Talebizadeh, Mansour; Vanrolleghem, Peter A. and Jeppsson, Ulf LU , et al. (2014) 4th IWA/WEF Wastewater Treatment Modelling Seminar, 2014
Abstract
The success of many modelling studies strongly depends on the availability of sufficiently

long influent time series - the main disturbance of a typical wastewater treatment plant (WWTP) -

representing the inherent natural variability at the plant inlet as accurately as possible. This is an

important point since most modelling projects suffer from a lack of realistic data representing the

influent wastewater dynamics. The objective of this paper is to show the advantages of creating

synthetic data when performing modelling studies for WWTPs. This study reviews the different

principles that influent generators can be based on, in order to create realistic influent time series. In... (More)
The success of many modelling studies strongly depends on the availability of sufficiently

long influent time series - the main disturbance of a typical wastewater treatment plant (WWTP) -

representing the inherent natural variability at the plant inlet as accurately as possible. This is an

important point since most modelling projects suffer from a lack of realistic data representing the

influent wastewater dynamics. The objective of this paper is to show the advantages of creating

synthetic data when performing modelling studies for WWTPs. This study reviews the different

principles that influent generators can be based on, in order to create realistic influent time series. In

addition, the paper summarizes the variables that those models can describe: influent flow rate,

temperature and traditional/emerging pollution compounds, weather conditions (dry/wet) as well as

their temporal resolution (from minutes to years). The importance of calibration/validation is

addressed and the authors critically analyse the pros and cons of manual versus automatic and

frequentistic vs Bayesian methods. The presentation will focus on potential engineering applications

of influent generators, illustrating the different model concepts with case studies. The authors have

significant experience using these types of tools and have worked on interesting case studies that they

will share with the audience. Discussion with experts at the WWTmod seminar shall facilitate

identifying critical knowledge gaps in current WWTP influent disturbance models. Finally, the

outcome of these discussions will be used to define specific tasks that should be tackled in the near

future to achieve more general acceptance and use of WWTP influent generators. (Less)
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Contribution to conference
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subject
keywords
Disturbance generators, dynamics, flow, influents, pollution loads, uncertainty
conference name
4th IWA/WEF Wastewater Treatment Modelling Seminar, 2014
language
English
LU publication?
yes
id
5b649e19-abf5-4991-ae4a-66cad6fe9b45 (old id 4352622)
alternative location
http://www.sanitas-itn.eu/wp-content/uploads/2014/02/Flores-Alsina-et-al_WWTPmod2014_final-version.pdf
date added to LUP
2014-03-10 10:35:14
date last changed
2016-04-16 10:38:07
@misc{5b649e19-abf5-4991-ae4a-66cad6fe9b45,
  abstract     = {The success of many modelling studies strongly depends on the availability of sufficiently <br/><br>
long influent time series - the main disturbance of a typical wastewater treatment plant (WWTP) - <br/><br>
representing the inherent natural variability at the plant inlet as accurately as possible. This is an <br/><br>
important point since most modelling projects suffer from a lack of realistic data representing the <br/><br>
influent wastewater dynamics. The objective of this paper is to show the advantages of creating <br/><br>
synthetic data when performing modelling studies for WWTPs. This study reviews the different <br/><br>
principles that influent generators can be based on, in order to create realistic influent time series. In <br/><br>
addition, the paper summarizes the variables that those models can describe: influent flow rate, <br/><br>
temperature and traditional/emerging pollution compounds, weather conditions (dry/wet) as well as <br/><br>
their temporal resolution (from minutes to years). The importance of calibration/validation is <br/><br>
addressed and the authors critically analyse the pros and cons of manual versus automatic and <br/><br>
frequentistic vs Bayesian methods. The presentation will focus on potential engineering applications <br/><br>
of influent generators, illustrating the different model concepts with case studies. The authors have <br/><br>
significant experience using these types of tools and have worked on interesting case studies that they <br/><br>
will share with the audience. Discussion with experts at the WWTmod seminar shall facilitate <br/><br>
identifying critical knowledge gaps in current WWTP influent disturbance models. Finally, the <br/><br>
outcome of these discussions will be used to define specific tasks that should be tackled in the near <br/><br>
future to achieve more general acceptance and use of WWTP influent generators.},
  author       = {Flores, Xavier and Ort, Cristoph and Martin, Cristina and Benedetti, Lorenzo and Belia, Evangelina and Snip, Laura and Saagi, Ramesh and Talebizadeh, Mansour and Vanrolleghem, Peter A. and Jeppsson, Ulf and Gernay, Krist V.},
  keyword      = {Disturbance generators,dynamics,flow,influents,pollution loads,uncertainty},
  language     = {eng},
  title        = {Generation of (synthetic) influent data for performing wastewater treatment modelling studies},
  year         = {2014},
}