9th International Conference on Urban Drainage Modelling Belgrade 2012

Integrated modelling for cost effective optimization of the urban wastewater system in the area Lorenzo Benedetti1, Jarno de Jonge2, Jeroen de Klein3, Tony Flameling2, Jeroen Langeveld4, Ingmar Nopens5, Arjen F. van Nieuwenhuijzen6, Oscar van Zanten2 and Stefan Weijers2

1WATERWAYS srl, Via del Ferrone 88, 50023 Impruneta, Italy (Email: [email protected]), 2Waterschap De Dommel, PO Box 10.001, 5280 DA , The (Email: [email protected], [email protected], [email protected], [email protected]), 3Aquatic Ecology and Water Quality Management, Wageningen University, PO Box 47 6700 Wageningen, The Netherlands (Email: [email protected]), 4Royal Haskoning/Delft University of Technology, PO Box 5048, Delft, The Netherlands (Email: [email protected]), 5BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, (Email: [email protected]), 6Witteveen+Bos, PO Box 233, NL-7400 AE Deventer, The Netherlands (Email: [email protected])

EXTENDED ABSTRACT Waterboard De Dommel intends to optimize the water flows within the Eindhoven cluster area to efficiently meet the requirements of the European Union Water Framework Directive (WFD). The targeted water flows consist of the combined storm- and wastewater of the City of Eindhoven and nine surrounding communities feeding the WWTP of Eindhoven. After biological nutrient removal, the effluent of the treatment plant is discharged into the Dommel River. Rainwater flow increases the flow to the treatment plant by a factor of more than five, of which part is treated in a parallel rainwater treatment line. During intense storm water events, about 200 combined sewer overflows (CSOs) may discharge the surplus of (polluted) storm water into the Dommel, affecting the chemical and ecological quality of the river negatively. Controlling the different water flows (i.e. where to send what water flow for optimal performance of the entire system) is a complex task, due to all required measures for monitoring, modeling, conveying and treating the water, and to administrative fragmentation. With the KALLISTO project (www.samenslimschoon.nl), an international consortium is approaching those problems differently using an integrated strategy. By applying an innovative combination of monitoring, modeling and controlling water flows and by constructing adequate technical measures like pumping and advanced treatment facilities, the storm and waste water flows will be actively controlled, conveyed and treated based on water quality and quantity (so-called impact-based control). Fundamental in this decision making and optimization framework is the water quality of the Dommel. For that reason, the water quality of the river, major CSOs, WWTP inlet and outlet are monitored continuously and modeled to be able to determine (depending on the actual situation) where, when and for how long discharge of effluent or overflow water is to be tolerated during major storm water events – using integrated real-time control (RTC) – or whether additional measures have to be taken. In this way, existing and new (to be built) transportation and treatment infrastructure is used optimally (from the river’s perspective).

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By applying this integrated and high technology approach, it is expected to save approximately 10% to 30% of the capital costs (estimated to be about 150 to 200 million EUR) in comparison to individual measures in a non-integrated approach. In this paper, the focus is on the description of the development of an integrated simplified sewer-WWTP-river integrated model. This model was necessary to run the required long- term and the many short-term simulations, which is not feasible with the detailed models. Previous and parallel work provided models of the sub-systems under study (sewer, WWTP and river) at high level of detail, calibrated and validated on data coming from historical measurements (not necessarily from the same period for the three systems) or dedicated campaigns within KALLISTO. The integrated model (in WEST) has: • for the sewers, TIS hydraulic model and simplification at spatial level, lumping catchments and modeling only significant pipes and overflows, resulting in 60 draining catchments and associated retention volumes, 8 trunk sewers and associated control structures and 30 CSOs; • for the WWTP, the model is the same as the detailed one, as it is already with TIS and with limited spatial complexity (13 activated sludge tanks plus settlers, buffers etc.), while the water quality model and all controllers do not need simplification; • for the river, also a TIS model is made for hydraulics, and the water quality model is identical to the detailed one; the spatial discretisation – 65 stretches (tanks) – depends on the significant inputs and on the river hydraulics. The above three simplified models were implemented independently and using data from simulations of the detailed models, and then integrated into a single executable model. This allows overcoming: • the communication problems between different software, reducing the possible scenarios to be run, especially regarding integrated RTC; • the simulation speed problem of the detailed models, allowing to reduce the time needed to run each (long term) scenario by several orders of magnitude; as an example, the complete integrated model simulates one year with hourly inputs and outputs in 13 minutes on a single 3.4 GHz processor. The development of specific interfaces between models was required. As quality modules in sewer models are still considered not sufficiently reliable, for the WWTP input an empirical model was developed using the long high frequency time series available from the sensors placed at the WWTP inlet, generating NH4, PO4, COD, CODs and TSS hourly time series in function of flow rate at the sewer outlet. For the CSO outputs into the river, an event mean concentration (EMC) was applied. This EMC has been derived from 2 years of monitoring data at two CSOs in Eindhoven. The model was used to perform a global sensitivity analysis (GSA) – using Monte Carlo simulations – of the operational parameters towards the receiving water quality evaluation criteria, to identify the “control-handles” with the highest potential in the system. The integrated model was then used to (1) test RTC strategies using the current infrastructure, (2) evaluate performance gaps (receiving water quality deficits) and then (3) test the effect of additional measures (volumes and treatments) to fill that gap.

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