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    THẠC SĨ A New Empirical Sewer Water Quality Model for the Prediction of WWTP Influent Quality

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  6. A New Empirical Sewer Water Quality Model for the Prediction of WWTP Influent Quality

    1

    A New Empirical Sewer Water Quality Model for the Prediction
    of WWTP Influent Quality

    Jeroen LANGEVELD
    1,2*
    , Remy SCHILPEROORT
    1
    , Petra VAN DAAL
    2,3
    , Lorenzo
    BENEDETTI
    4
    , Youri AMERLINCK
    5
    , Jarno DE JONGE
    6
    , Tony FLAMELING
    6
    , Ingmar
    NOPENS
    5
    , Stefan WEIJERS
    5,6


    1
    Royal Haskoning DHV, P.O. Box 151, 6500 AD, Nijmegen, The Netherlands

    2
    Delft University of Technology, PO Box 5048, Delft, The Netherlands

    3
    Witteveen+Bos, P.O. Box 233, 7400 AE Deventer, The Netherlands

    4
    WATERWAYS srl, Via del Ferrone 88, 50023 Impruneta, Italy

    5
    BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent
    University, Coupure Links 653, 9000 Gent, Belgium

    6
    Waterschap De Dommel, P.O. Box 10.001, 5280 DA, Boxtel, The Netherlands
    *
    Corresponding author
    Email: j.g.langeveld@tudelft.nl

    ABSTRACT
    Modelling of the integrated urban water system is a powerful tool to optimise wastewater
    system performance or to find cost-effective solutions for receiving water problems. One of
    the challenges of integrated modelling is the prediction of water quality at the inlet of a
    WWTP. Recent applications of water quality sensors have resulted in the availability of long
    time series of sewer water quality and WWTP influent quality. This time series contains a lot
    of information on the response of sewer water quality to, for example, storm events. This
    allows the development of empirical models to predict sewer water quality. This paper
    proposes a new approach for water quality modelling, which uses the measured hydraulic
    dynamics at the influent of the WWTP to derive the (measured) influent water quality. This
    model can then be used as a WWTP influent generator using either measured or simulated
    influent hydraulics as input.

    KEYWORDS
    Sewer system, empirical model, influent generator, water quality modelling

    INTRODUCTION
    Modelling of the integrated urban water system is a powerful tool to optimise wastewater
    system performance or to find cost effective solutions for receiving water problems
    (Benedetti et al., 2013a). One of the weaknesses of integrated modelling is the water quality
    modelling in sewer systems, due to the limited knowledge on the physical-chemical,
    biological and transport processes occurring in sewer systems (Bertrand-Krajewski, 2007).
    Especially sediment transport is not very well understood and not very successfully
    reproduced in deterministic models. This is partly due to the fact that it is currently not
    possible to get enough data on the initial sewer sediment conditions throughout an entire
    sewer network. As a consequence, a lot of effort has been put in the development of
    regression models, which are validated against monitoring data. A recent successful example
    of this approach is given by Dembélé et al. (2011), who developed an empirical model for
    stormwater total suspended solids (TSS) event mean concentrations with rainfall depth and
    antecedent dry weather period as input variables. These empirical relations, that are valid at a
    combined sewer overflow (CSO) or storm sewer outfall (SSO), however, are not suitable for 13
    th
    International Conference on Urban Drainage, Sarawak, Malaysia, 7-12 September 2014
    2

    the prediction of wastewater treatment plant (WWTP) influent quality, as these models do not
    predict the influent quality during dry weather flow (DWF).
    Recent applications of water quality sensors have resulted in the availability of long time
    series of sewer water quality and WWTP influent quality. These time series contain a lot of
    information on the response of sewer water quality to e.g. storm events. This allows the
    development of empirical models to predict sewer water quality at the inlet of a WWTP, such
    as for example the one by Talebizadeh et al. (2014). They use a mix of statistical and
    conceptual modeling techniques for synthetic generation of influent time series based on a
    periodic multivariate time series model for the influent in DWF conditions and a two-state
    Markov chain-gamma model for rainfall conditions. The main drawback of this approach is
    that the errors in the hydrologic runoff and hydraulic sewer model cumulate. In order to
    overcome this drawback, a new approach is developed and presented in this paper, which
    uses the measured hydraulic behaviour at the influent of the WWTP to derive the (measured)
    influent water quality. This model can then be used to predict WWTP influent water quality
    using simulated influent hydraulics as input.
    This paper describes the development of this new model for the WWTP Eindhoven in the
    Netherlands, with flow and water level as the input variables. The paper also discusses the
    transferability of the developed concept to other locations.

    METHODS AND MATERIALS

    System description: the Dommel River IUWS
    The Dommel is a relatively small and sensitive river flowing through the city of Eindhoven
    (The Netherlands) from the Belgian border (South) into the river Meuse (North), receiving
    discharges from the 750,000 PE wastewater treatment plant (WWTP) of Eindhoven and from
    over 200 combined sewer overflows (CSOs) in 10 municipalities. In summer, the WWTP
    effluent equals the base flow of 1.5 m
    3
    /s of the Dommel River just upstream the WWTP. The
    Dommel River does not yet meet the requirements of the European Union Water Framework
    Directive (WFD). The water quality issues to be addressed are dissolved oxygen (DO)
    depletion, ammonia peaks and seasonal average nutrient concentration levels (Weijers et al.
    2012). Benedetti et al. (2013b) describe the set of measures required for compliance with the
    WFD and the methodology applied to derive them as developed in the KALLISTO project.

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