Generation of diurnal variation for influent data for dynamic simulation

Institute of Sanitary Engineering and Water Pollution Control, University of Natural Resources and Applied Life Sciences, Vienna BOKU, Muthgasse 18, A-1190 Vienna, Austria.
Water Science & Technology (Impact Factor: 1.11). 02/2008; 57(9):1483-6. DOI: 10.2166/wst.2008.228
Source: PubMed


When using dynamic simulation for fine tuning of the design of activated sludge (AS) plants diurnal variations of influent data are required. For this application usually only data from the design process and no measured data are available. In this paper a simple method to generate diurnal variations of wastewater flow and concentrations is described. The aim is to generate realistic influent data in terms of flow, concentrations and TKN/COD ratios and not to predict the influent of the AS plant in detail. The work has been prepared within the framework of HSG-Sim (Hochschulgruppe Simulation,, a group of researchers from Germany, Austria, Luxembourg, Poland, the Netherlands and Switzerland.

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Available from: Norbert Weissenbacher, Mar 20, 2014
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    • ". (from Langergraber et al., 2008 "
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    ABSTRACT: This 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.). (C) 2014 Published by Elsevier Ltd.
    Environmental Modelling and Software 10/2014; 60:188–201. DOI:10.1016/j.envsoft.2014.05.008 · 4.42 Impact Factor
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    • "In this case, a dynamic model has limited informative power as information on load and temperature variation and the specific dynamics of the system are not available or can only be derived through estimations. Influent generators (Langergraber et al., 2008; Gernaey et al., 2006), taking connected population equivalents (PE) and sewer system specifics into account, may help to get a better understanding of the dynamics of the planned system. "
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    ABSTRACT: Building an aeration system requires a major investment, with blowers typically being the single most costly piece of equipment at a WWTP. Aeration is also responsible for about 50-60 % of the total energy demand for an activated sludge plant. Moreover the DO concentration controls which processes are active or kinetically limited. The investment and operational costs, together with the impact of aeration on the treatment performance, highlight the need for a careful design of this essential part of every activated sludge treatment plant. Because oxygen transfer and oxygen demand are highly dynamic and directly linked to variations in influent load, temperature, etc., dynamic models should be used in the design process. This paper describes current practice, discusses available models and links models to specific objectives.
    01/2012; 2012(7):7409-7414. DOI:10.2175/193864712811703702
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    • "Dynamic influent flow rate data can be generated by means of a simple equation, such as a Fourier series (sum of sinusoids with varying frequencies and phase shifts) whose parameters are fitted to dynamic influent data (e.g. Carstensen et al., 1998; Langergraber et al., 2008; Alex et al., 2009), by means of a more sophisticated model (e.g. Gernaey et al., 2005; Béraud et al., 2007) or by a very complex and detailed deterministic model of the complete catchment area (e.g. "
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    ABSTRACT: Activated Sludge Models are widely used for simulation-based evaluation of wastewater treatment plant (WWTP) performance. However, due to the high workload and cost of a measuring campaign on a full-scale WWTP, many simulation studies suffer from lack of sufficiently long influent flow rate and concentration time series representing realistic wastewater influent dynamics. In this paper, a simple phenomenological modelling approach is proposed as an alternative to generate dynamic influent pollutant disturbance scenarios. The presented set of models is constructed following the principles of parsimony (limiting the number of parameters as much as possible), transparency (using parameters with physical meaning where possible) and flexibility (easily extendable to other applications where long dynamic influent time series are needed). The proposed approach is sub-divided in four main model blocks: 1) model block for flow rate generation, 2) model block for pollutants generation (carbon, nitrogen and phosphorus), 3) model block for temperature generation and 4) model block for transport of water and pollutants. The paper is illustrated with the results obtained during the development of the dynamic influent of the Benchmark Simulation Model no. 2 (BSM2). The series of simulations show that it is possible to generate a dry weather influent describing diurnal flow rate dynamics (low rate at night, high rate during day time), weekend effects (with different flow rate during weekends, compared to weekdays), holiday effects (where the wastewater production is assumed to be different for a number of weeks) and seasonal effects (with variations in the infiltration and thus also the flow rate to the WWTP). In addition, the dry weather model can be extended with a rain and storm weather generator, where the proposed phenomenological model can also mimic the “first flush” effect from the sewer network and the influent dilution phenomena that are typically observed at full-scale WWTPs following a rain event. Finally, the extension of the sewer system can be incorporated in the influent dynamics as well: the larger the simulated sewer network, the smoother the simulated diurnal flow rate and concentration variations. In the discussion, it is pointed out how the proposed phenomenological models can be expanded to other applications, for example to represent heavy metal or organic micro-pollutant loads entering the treatment plant.
    Environmental Modelling and Software 11/2011; 26(11). DOI:10.1016/j.envsoft.2011.06.001 · 4.42 Impact Factor
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