Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Modular Conceptual Modelling Approach and Software for Sewer Hydraulic Computations

  • 435 Accesses

  • 9 Citations


A major challenge in urban water management is the identification of cost-effective and future-proof strategies that can cope with the rapid urbanization and changing environmental conditions. Water quantity modelling forms a key-element in the development of such strategies. Conventional detailed hydrodynamic models are not well suited for use in decision support systems due to several important drawbacks. Therefore, this paper presents a novel and computationally efficient conceptual modelling approach for sewer water quantity simulations. A modular framework is considered that combines well-established model structures with machine learning techniques. This flexible framework ensures that even complex flow dynamics can be emulated accurately. An accompanying software tool was developed to facilitate model configuration. As an example, a full hydrodynamic sewer model of a city in Belgium was transformed into a conceptual model. This model delivered precise results, while the calculation time was 106 times shorter than the detailed model.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6


  1. Achleitner S, Fach S, Einfalt T, Rauch W (2009) Nowcasting of rainfall and of combined sewage flow in urban drainage systems. Water Sci Technol 59(6):1145–1151

  2. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19(6):716–723

  3. Bach PM, Rauch W, Mikkelsen PS, McCarty DT, Deletic A (2014) A critical review of integrated urban water modelling – urban drainage and beyond. Environ Model Softw 54:88–107

  4. Bujon G, Herremans L, Phan L (1992) FLUPOL: a forecasting model for flow and pollutant discharge from sewerage systems during rainfall events. Water Sci Technol 25(8):207–215

  5. Burger G, Fach S, Kinzel H, Rauch W (2010) Parallel computing in conceptual sewer simulations. Water Sci Technol 61(2):283–291

  6. Chiang PK, Willems P (2013) Model conceptualization procedure for river (flood) hydraulic computations: case study of the Demer River, Belgium. Water Resour Manag 27(12):4277–4289

  7. De Vleeschauwer K, Weustenraad J, Nolf C, Wolfs V, De Meulder B, Shannon K, Willems P (2014) Green-blue water in the city: quantification of impact of source control versus end-of-pipe solutions on sewer and river floods. Water Sci Technol 70(11):1825–1837

  8. Dirckx G, Schütze M, Kroll S, Thoeye C, De Gueldre G, Van De Steene B (2011) Cost-efficiency of RTC for CSO impact mitigation. Urban Water J 8(6):367–377

  9. Freni G, Mannina G, Viviani G (2010) Urban water quality modelling: a parsimonious holistic approach for a complex real case study. Water Sci Technol 61(2):521–536

  10. ITWH (2000) KOSIM 6.2. Anwenderhandbuch. Institut für technisch-wissenschaftliche Hydrologie GmbH, Hannover, Germany

  11. Keupers I, Wolfs V, Kroll S, Willems P (2015) Impact analysis of sewer emissions on the receiving river water quality using an integrated conceptual model. Proceedings of the 10th International Urban Drainage Modelling (UDM) Conference. Québec, Canada, September 20–23 2015

  12. Kleidorfer M, Deletic A, Fletcher TD, Rauch W (2009) Impact of input data uncertainties on urban stormwater model parameters. Water Sci Technol 60:1545–1554

  13. Maier HR, Jain A, Dandy G, Sudheer KP (2010) Methods used for the development of neural networks for the prediction of water resource variables in river systems: current status and future directions. Environ Model Softw 25:891–909

  14. Muschalla D, Reussner F, Schneider S, Ostrowski MW (2006) Dokumentation des Schmutzfrachtmodells SMUSI Version 5.0. Institut für Wasserbau und Wasserwirtschaft, Technische Unversität Darmstadt, Germany. (In German)

  15. Nagesh Kumar D, Srinivasa Raju K, Sathish T (2004) River flow forecasting using recurrent neural networks. Water Resour Manag 18:143–161

  16. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I – a discussion of principles. J Hydrol 10(3):282–290

  17. Savic DA, Walters GA, Davidson JW (1999) A genetic programming approach to rainfall-runoff modelling. Water Resour Manag 13:219–231

  18. Schütze M, Campisano A, Colas H, Schilling W, Vanrolleghem PA (2004) Real time control of urban wastewater systems – where do we stand today? J Hydrol 299:335–348

  19. Solvi A-M (2007) Modelling the sewer-treatment-urban river system in view of the EU Water Framework Directive. PhD thesis, Ghent University, Belgium, pp. 218

  20. Vaes G (1999) The influence of rainfall and model simplification on combined sewer system design. PhD Thesis, Department of Civil Engineering. University of Leuven, Belgium

  21. Vanrolleghem PA, Benedetti L, Meirlaen J (2005) Modelling and real-time control of the integrated urban wastewater system. Environ Model Softw 20:427–442

  22. Vezzaro L, Christensen ML, Thirsing C, Grum M, Mikkelsen PS (2014) Water quality-based real time control of integrated urban drainage systems: a preliminary study from Copenhagen, Denmark. Procedia Eng 70:1707–1716

  23. Voinov A, Shugart H (2013) ‘Integronsters’, integral and integrated modeling. Environ Model Softw 39:149–158

  24. Vojinovic Z, Seyoum SD (2008) Integrated urban water systems modelling with a simplified surrogate modular approach. In: 11th International Conference on Urban Drainage. Edinburgh, Scotland, UK

  25. Willems P, Olsson J, Arnbjerg-Nielsen K, Beecham S, Pathirana A, Bülow Gregersen I, Madsen H, Nguyen V-T-V (2012) Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, London

  26. Wolfs V, Willems P (2014) Development of discharge-stages curves affected by hysteresis using time varying models, model tree and neural networks. Environ Model Softw 55:107–119

  27. Wolfs V, Villazon MF, Willems P (2013) Development of a semi-automated model identification and calibration tool for conceptual modelling of sewer systems. Water Sci Technol 68(1):167–175

  28. Wolfs V, Meert P, Willems P (2015) Modular conceptual modelling approach and software for river hydraulic computations. Environ Model Softw 71:60–77

  29. Wolfs V, Ntegeka V, Murla Tuyls D, Willems P (2016) Development of a computationally efficient urban flood modelling approach. In: Proceedings of the 4th IAHR Europe Congress, Liege, Belgium, 27–29 July 2016

  30. Zoppou C (2001) Review of urban storm water models. Environ Model Softw 16:195–231

Download references


This research was supported by the Agency for Innovation by Science and Technology in Flanders (IWT). The authors would like to thank Innovyze for the InfoWorks CS license. Farys is gratefully acknowledged for providing the InfoWorks CS model used in the case study.

Author information

Correspondence to Vincent Wolfs.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wolfs, V., Willems, P. Modular Conceptual Modelling Approach and Software for Sewer Hydraulic Computations. Water Resour Manage 31, 283–298 (2017).

Download citation


  • Computational hydraulics
  • Decision support systems
  • Modelling
  • Urban drainage
  • Water management