Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

Flores-Alsina, Xavier; Saagi, Ramesh; Lindblom, Erik; Thirsing, Carsten; Thornberg, Dines; Gernaey, Krist V.; Jeppsson, Ulf

doi:10.1016/j.watres.2013.10.022

Cited by 37 publications

(18 citation statements)

References 44 publications

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“…Water 2017, 9,491For WWF, it has been observed that the concentration levels of the wastewater show a typical pattern during a storm event: a short period called 'onset' of the storm event, with an increased concentration level for particulate matter but not for dissolved matter, a longer period called 'dilution', where dilution of both dissolved and particulate matter takes place, and 'recovery', a period where dissolved and particulate matter slowly return to DWF levels.…”

Section: Model Developmentmentioning

confidence: 99%

“…In other words, the influent model can be applied on measured or simulated hydraulics and may also be applied in combination with the harmonic functions described in the introduction. Moreover, as the empirical influent model is developed to adequately mimic WWF dynamics, it might be included in the phenomenological influent pollutant disturbance scenario generator [9], which is the latest version of the phenomenological model developed by [8], replacing the relatively weak sewer model module of this model.…”

Section: Applications: Influent Generation Surveillance Of Monitorinmentioning

confidence: 99%

“…In a comprehensive review, [7] discussed the available approaches for generating influent data. The approaches range from (1) data driven methods based on creating databases with monitoring and experimental data and derived models using the data; (2) very simple models based on harmonic functions; and (3) phenomenological models [8,9].…”

Section: Introductionmentioning

confidence: 99%

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Empirical Sewer Water Quality Model for Generating Influent Data for WWTP Modelling

Langeveld

Daal

Schilperoort³

et al. 2017

Water

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Wastewater treatment plants (WWTP) typically have a service life of several decades. During this service life, external factors, such as changes in the effluent standards or the loading of the WWTP may change, requiring WWTP performance to be optimized. WWTP modelling is widely accepted as a means to assess and optimize WWTP performance. One of the challenges for WWTP modelling remains the prediction of water quality at the inlet of a WWTP. Recent applications of water quality sensors have resulted in long time series of WWTP influent quality, containing valuable information on the response of influent quality to e.g., storm events. This allows the development of empirical models to predict influent quality. This paper proposes a new approach for water quality modelling, which uses the measured hydraulic dynamics of the WWTP influent to derive the influent water quality. The model can also be based on simulated influent hydraulics as input. Possible applications of the model are filling gaps in time series used as input for WWTP models or to assess the impact of measures such as real time control (RTC) on the performance of wastewater systems.

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Section: Model Developmentmentioning

confidence: 99%

Section: Applications: Influent Generation Surveillance Of Monitorinmentioning

confidence: 99%

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Empirical Sewer Water Quality Model for Generating Influent Data for WWTP Modelling

Langeveld

Daal

Schilperoort³

et al. 2017

Water

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“…This is achieved by combining three user-defined data files containing: 1) a normalized daily profile; 2) a weekly pattern including the weekend effect; and, 3) a holiday effect. The generated time series is then multiplied by the flow rate/pollution load per population equivalent (m 3 /PE.day, kg/PE.day) and the number of person equivalents in the specific subcatchment (PE i ) (for default values see Gernaey et al, 2011;Flores-Alsina et al, 2014;Snip et al, 2014).…”

Section: Domestic (Dom)mentioning

confidence: 99%

Catchment & sewer network simulation model to benchmark control strategies within urban wastewater systems

Saagi

Flores-Alsina

et al. 2016

Environmental Modelling & Software

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“…In order to decrease the computational effort, parameters that could be estimated manually were excluded from the procedure. As has been shown by Flores-Alsina et al (2014) the influent generator uses many non-identifiable parameters, which would increase the computational burden of an automatic calibration. Another possibility for the automatic calibration could be the Bayesian technique.…”

Section: Calibration Proceduresmentioning

confidence: 99%

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

Snip

Flores-Alsina

Aymerich

et al. 2016

Science of The Total Environment

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The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2-4h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The 'traditional' variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities.

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Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

Cited by 37 publications

References 44 publications

Empirical Sewer Water Quality Model for Generating Influent Data for WWTP Modelling

Empirical Sewer Water Quality Model for Generating Influent Data for WWTP Modelling

Catchment & sewer network simulation model to benchmark control strategies within urban wastewater systems

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

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