Analysing, completing, and generating influent data for WWTP modelling: a critical review

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dc.contributor.authorMartín Andonegui, Cristina
dc.contributor.authorVanrolleghem, Peter A.
dc.date.accessioned2026-04-23T12:00:24Z
dc.date.available2026-04-23T12:00:24Z
dc.date.issued2014-10
dc.date.updated2026-04-23T12:00:24Z
dc.description.abstractThis paper makes a critical review of the available techniques for analysing, completing and generating influent data for WWTP modelling. The solutions found in literature are classified according to three different situations from engineering practice: 1) completing an incomplete dataset about the quantity and quality of the influent wastewater; 2) translating the common quality measurements (COD, TSS, TKN, etc.) into the ASM family components (fractionation problem); 3) characterising the uncertainty in the quality and quantity of the influent wastewater. In the first case (Situation 1), generators based on Fourier models are very useful to describe the daily and weekly wastewater patterns. Another specially promising solution is related to the construction of phenomenological models that provide wastewater influent profiles in accordance with data about the catchment properties (number of inhabitant equivalents, sewer network, type of industries, rainfall and temperature profiles, etc.). This option has the advantage that using hypothetical catchment characteristics (other climate, sewer network, etc.) the modeller is able to extrapolate and generate influent data for WWTPs in other scenarios. With a much lower modelling effort, the generators based on the use of databases can provide realistic influent profiles based on the patterns observed. With regard to the influent characterisation (Situation 2), the WWTP modelling protocols summarise well established methodologies to translate the common measurements (COD, TSS, TKN, etc.) into ASM family components. Finally, some statistical models based on autoregressive functions are suitable to represent the uncertainty involved in influent data profiles (Situation 3). However, more fundamental research should be carried out to model the uncertainty involved in the underlying mechanisms related to the wastewater generation (rainfall profiles, household and industries pollutant discharges, assumed daily and weekly patterns, etc.).en
dc.description.sponsorshipThis work was made possible through the financial support of the Hampton Roads Sanitation District, Virginia, USA. The authors wish to acknowledge the support provided by the IWA Task Group on Design and Operations Uncertainty (DOUT Specialist Task Group) and the engineering experience of Evangelia Belia from Primodal Inc, Quebec, QC, Canada. The authors wish also to thank the financial support of the Natural Science and Engineering Research Council of Canada (NSERC). Peter A. Vanrolleghem holds the Canada Research Chair in Water Quality Modelingen
dc.identifier.citationMartin, C., & Vanrolleghem, P. A. (2014). Analysing, completing, and generating influent data for WWTP modelling: a critical review. Environmental Modelling and Software, 60, 188-201. Elsevier Ltd. https://doi.org/10.1016/J.ENVSOFT.2014.05.008
dc.identifier.doi10.1016/J.ENVSOFT.2014.05.008
dc.identifier.issn1364-8152
dc.identifier.urihttps://hdl.handle.net/20.500.14454/5749
dc.language.isoeng
dc.publisherElsevier Ltd
dc.rights© 2014 Published by Elsevier Ltd.
dc.subject.otherActivated sludge models
dc.subject.otherInfluent disturbance model
dc.subject.otherInfluent generator
dc.subject.otherPhenomenological model
dc.subject.otherProbabilistic design
dc.subject.otherUncertainty assessment
dc.titleAnalysing, completing, and generating influent data for WWTP modelling: a critical reviewen
dc.typereview article
dcterms.accessRightsopen access
oaire.citation.endPage201
oaire.citation.startPage188
oaire.citation.titleEnvironmental Modelling and Software
oaire.citation.volume60
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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