A Comprehensive Approach to Stormwater Management Problems in the Next Generation Drainage Networks

  • Patrizia Piro
  • Michele TurcoEmail author
  • Stefania Anna Palermo
  • Francesca Principato
  • Giuseppe Brunetti
Part of the Internet of Things book series (ITTCC)


In an urban environment, sewer flooding and combined sewer overflows (CSOs) are a potential risk to human life, economic assets and the environment. In this way, traditional urban drainage techniques seem to be inadequate for the purpose so to mitigate such phenomena, new techniques such as Real Time Control (RTC) of urban drainage systems and Low Impact Development (LID) techniques represent a valid and cost-effective solution. This chapter lists some of the recent experiences in the field of Urban Hydrology consisting in a series of facilities, fully equipped with sensors and other electronical component, to prevent flooding in urban areas. A series of innovative numerical analysis (in Urban Hydrology research) have been proposed to define properties of the hydrological/hydraulic models used to reproduce the natural processes involved.


  1. 1.
    S. Achleitner, M. Möderl, W. Rauch, CITY DRAIN ©—an open source approach for simulation of integrated urban drainage systems. Environ. Model. Softw. 22, 1184–1195 (2007). Scholar
  2. 2.
    R.G. Allen, L.S. Pereira, D. Raes, M. Smith, FAO Irrigation and Drainage Paper No. 56: Crop Evapotranspiration, FAO. Rome (1998)Google Scholar
  3. 3.
    G.E.B. Archer, A. Saltelli, I.M. Sobol, Sensitivity measures, ANOVA-like techniques and the use of bootstrap. J. Stat. Comput. Simul. 58, 99–120 (1997). Scholar
  4. 4.
    K. Astrom, PID controllers: theory, design and tuning. Instrum. Soc. Am. (1995). ISBN 1556175167Google Scholar
  5. 5.
    P.M. Bach, W. Rauch, P.S. Mikkelsen, D.T. McCarthy, A. Deletic, A critical review of integrated urban water modelling—urban drainage and beyond. Environ. Model. Softw. (2014).
  6. 6.
    G. Barenblatt, I. Zheltov, I. Kochina, Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]. J. Appl. Math. Mech. 24, 1286–1303 (1960). Scholar
  7. 7.
    T. Beeneken, V. Erbe, A. Messmer, C. Reder, R. Rohlfing, M. Scheer, M. Schuetze, B. Schumacher, M. Weilandt, M. Weyand, Real time control (RTC) of urban drainage systems—a discussion of the additional efforts compared to conventionally operated systems. Urban Water J. 10, 293–299 (2013). Scholar
  8. 8.
    G. Brunetti, J. Simunek, P. Piro, A comprehensive analysis of the variably-saturated hydraulic behavior of a green roof in a mediterranean climate. Vadose Zo. J. 15 (in press) (2016a).
  9. 9.
    G. Brunetti, J. Šimůnek, P. Piro, A comprehensive numerical analysis of the hydraulic behavior of a permeable pavement. J. Hydrol. 540, 1146–1161 (2016). Scholar
  10. 10.
    G. Brunetti, J. Šimůnek, M. Turco, P. Piro, On the use of surrogate-based modeling for the numerical analysis of low impact development techniques. J. Hydrol. 548, 263–277 (2017). Scholar
  11. 11.
    M. Carbone, F. Principato, G. Garofalo, P. Piro, Comparison of evapotranspiration computation by FAO-56 and Hargreaves methods. J. Irrig. Drain. Eng. 142(8), 06016007 (2016). Scholar
  12. 12.
    M. Carbone, G. Brunetti, P. Piro, Modelling the hydraulic behaviour of growing media with the explicit finite volume solution. Water (Switzerland) 7, 568–591 (2015). Scholar
  13. 13.
    M. Carbone, M. Turco, G. Brunetti, P. Piro, A cumulative rainfall function for subhourly design storm in mediterranean urban areas. Adv. Meteorol. 2015, 1–10 (2015). Scholar
  14. 14.
    M. Carbone, M. Turco, G. Nigro, P. Piro, Modeling of hydraulic behaviour of green roof in catchment scale, in 14th SGEM GeoConference on Water Resources. Forest, Marine and Ocean Ecosystems (2014a), pp. 471–478.
  15. 15.
    M. Carbone, F. Principato, G. Nigro, P. Piro, Proposal of a conceptual model as tool for the hydraulic design of vegetated roof, in Applied Mechanics and Materials, vol. 641 (Trans Tech Publications, 2014b), pp. 326–331.
  16. 16.
    M. Carbone, G. Garofalo, P. Piro, Decentralized real time control in combined sewer system by using smart objects. Procedia Eng. 473–478 (2014c).
  17. 17.
    M. Carini, M. Maiolo, D. Pantusa, F. Chiaravalloti, G. Capano, Modelling and optimization of least-cost water distribution networks with multiple supply sources and user. Ricerche Mat. 2017 (2017).
  18. 18.
    B. Cheviron, Y. Coquet, Sensitivity analysis of transient-MIM HYDRUS-1D: case study related to pesticide fate in soils. Vadose Zo. J. 8, 1064 (2009). Scholar
  19. 19.
    G. Dirckx, M. Schütze, S. Kroll, C. Thoeye, G. De Gueldre, B. Van De Steene, Cost-efficiency of RTC for CSO impact mitigation. Urban Water J. 8, 367–377 (2011). Scholar
  20. 20.
    W. Durner, Hydraulic conductivity estimation for soils with heterogeneous pore structure. Water Resour. Res. 30, 211–223 (1994). Scholar
  21. 21.
    B. Efron, R. Tibshirani, Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Stat. Sci. 1, 54–75 (1986)MathSciNetCrossRefGoogle Scholar
  22. 22.
    A.H. Elliott, S.A. Trowsdale, A review of models for low impact urban stormwater drainage. Environ. Model. & Softw. 22, 394–405 (2007). Scholar
  23. 23.
    G. Fu, D. Butler, S.-T. Khu, Multiple objective optimal control of integrated urban wastewater systems. Environ. Model Softw. 23, 225–234 (2008). Scholar
  24. 24.
    A. Giordano, G. Spezzano, A. Vinci, G. Garofalo, P. Piro, A cyber-physical system for distributed real-time control of urban drainage networks in smart cities, in International Conference on Internet and Distributed Computing Systems (Springer, Cham, 2014), pp. 87–98.
  25. 25.
    G. Garofalo, A. Giordano, P. Piro, G. Spezzano, A. Vinci, A distributed real-time approach for mitigating CSO and flooding in urban drainage systems. J. Netw. Comput. Appl. 78, 30–42 (2017). Scholar
  26. 26.
    G. Garofalo, S. Palermo, F. Principato, T. Theodosiou, P. Piro, The influence of hydrologic parameters on the hydraulic efficiency of an extensive green roof in mediterranean area. Water 8(2), 44 (2016). Scholar
  27. 27.
    M.K. Gill, Y.H. Kaheil, A. Khalil, M. McKee, L. Bastidas, Multiobjective particle swarm optimization for parameter estimation in hydrology. Water Resour. Res. 42, n/a–n/a (2006).
  28. 28.
    T. Houska, S. Multsch, P. Kraft, H.-G. Frede, L. Breuer, Monte Carlo based calibration and uncertainty analysis of a coupled plant growth and hydrological model. Biogeosci. Discuss. 10, 19509–19540 (2013). Scholar
  29. 29.
    J. Huang, J. He, C. Valeo, A. Chu, Temporal evolution modeling of hydraulic and water quality performance of permeable pavements. J. Hydrol. 533, 15–27 (2016). Scholar
  30. 30.
    M. Jelasity, A. Montresor, O. Babaoglu, Gossip-based aggregation in large dynamic networks. ACM Trans. Comput. Syst. 23, 219–252 (2005). Scholar
  31. 31.
    Y. Jiang, C. Liu, C. Huang, X. Wu, Improved particle swarm algorithm for hydrological parameter optimization. Appl. Math. Comput. 217, 3207–3215 (2010). Scholar
  32. 32.
    M. Kamali, M. Delkash, M. Tajrishy, Evaluation of permeable pavement responses to urban surface runoff. J. Environ. Manag. 187, 43–53 (2017). Scholar
  33. 33.
    J. Kennedy, R. Eberhart, Particle swarm optimization. Eng. Technol. 1942–1948 (1995)Google Scholar
  34. 34.
    Z.W. Kundzewicz, M. Radziejewski, I. Pińskwar, Precipitation extremes in the changing climate of Europe. Clim. Res. 31, 51–58 (2006). Scholar
  35. 35.
    R. Levinson, H. Akbari, Effects of composition and exposure on the solar reflectance of portland cement concrete. Cem. Concr. Res. 32, 1679–1698 (2002). Scholar
  36. 36.
    Y. Li, R.W. Babcock, Green roof hydrologic performance and modeling: A review (Technol, Water Sci, 2014). Scholar
  37. 37.
    M. Maiolo, D. Pantusa, An optimization procedure for the sustainable management of water resources. Water Sci. Technol.: Water Supply 16(1), 61–69 (2016).
  38. 38.
    S.K. Min, X. Zhang, F.W. Zwiers, G.C. Hegerl, Human contribution to more-intense precipitation extremes. Nature 470, 378–381 (2011). Scholar
  39. 39.
    D.N. Moriasi, J.G. Arnold, M.W. Van Liew, R.L. Binger, R.D. Harmel, T.L. Veith, Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE 50, 885–900 (2007). Scholar
  40. 40.
    J.E. Nash, J.V. Sutcliffe, River flow forecasting through conceptual models Part I—A discussion of principles. J. Hydrol. 10, 282–290 (1970). Scholar
  41. 41.
    T. Pertassek, A. Peters, W. Durner, HYPROP-FIT Software User’s Manual, V.3.0 (2015)Google Scholar
  42. 42.
    P. Piro, M. Carbone, A modelling approach to assessing variations of total suspended solids (TSS) mass fluxes during storm events. Hydrol. Process. 28, 2419–2426 (2014). Scholar
  43. 43.
    P. Piro, M. Carbone, G. Garofalo, Distributed vs. concentrated storage options for controlling CSO volumes and pollutant loads. Water Pract. Technol. 5, wpt2010071–wpt2010071 (2010a).
  44. 44.
    P. Piro, M. Carbone, G. Garofalo, J. Sansalone, Size distribution of wet weather and dry weather particulate matter entrained in combined flows from an urbanizing sewershed. Water Air Soil Pollut. 206, 83–94 (2010). Scholar
  45. 45.
    M. Pleau, H. Colas, P. Lavallée, G. Pelletier, R. Bonin, Global optimal real-time control of the Quebec urban drainage system. Environ. Model. Softw. (2005).
  46. 46.
    F. Principato, S.A. Palermo, G. Nigro, G. Garofalo, Sustainable strategies and RTC to mitigate CSO’s impact: different scenarios in the highly urbanized catchment of Cosenza, Italy, in Proceedings of the 14th IWA/IAHR International Conference on Urban Drainage, ICUD2017, Prague, CZ, 10–15 Sept 2017, Oral Presentation, pp. 587–589Google Scholar
  47. 47.
    A. Raimondi, G. Becciu, On pre-filling probability of flood control detention facilities. Urban Water J. 12, 344–351 (2015). Scholar
  48. 48.
    A. Raimondi, G. Becciu, Probabilistic modeling of rainwater tanks. Procedia Eng. 89, 1493–1499 (2014). Scholar
  49. 49.
    M. Rezaei, P. Seuntjens, I. Joris, W. Boënne, S. Van Hoey, P. Campling, W.M. Cornelis, Sensitivity of water stress in a two-layered sandy grassland soil to variations in groundwater depth and soil hydraulic parameters. Hydrol. Earth Syst. Sci. Discuss. 12, 6881–6920 (2015). Scholar
  50. 50.
    L.A. Rossman, Storm water management model quality assurance report: dynamic wave flow routing. Storm Water Manag. Model Qual. Assur. Rep. 1–115 (2006)Google Scholar
  51. 51.
    A. Saltelli,, S. Tarantola, M. Saisana, M. Nardo, What is sensitivity analysis?, in II Convegno Della Rete Dei Nuclei Di Valutazione E Verifica, Napoli 26, 27 Gennaio 2005, Centro Congressi Universitá Federico II, Via Partenope 36 (2005)Google Scholar
  52. 52.
    M. Schütze, A. Campisano, H. Colas, W. Schilling, P.A. Vanrolleghem, Real time control of urban wastewater systems—where do we stand today? J. Hydrol. 299, 335–348 (2004). Scholar
  53. 53.
    N. She, J. Pang, Physically based green roof model. J. Hydrol. Eng. 15, 458–464 (2010). Scholar
  54. 54.
    J. Šimůnek, M.T. van Genuchten, M. Šejna, Recent developments and applications of the HYDRUS Computer Software Pac. Vadose Zo. J. 15, 25 (2016). Scholar
  55. 55.
    J. Simunek, N.J. Jarvis, M.T. van Genuchten, A. Gardenas, Review and comparison of models for describing non-equilibrium and preferential flow and transport in the vadose zone. J. Hydrol. 272, 14–35 (2003). Scholar
  56. 56.
    J. Šimůnek, M.T. van Genuchten, Modeling nonequilibrium flow and transport processes using HYDRUS. Vadose Zo. J. 7, 782 (2008). Scholar
  57. 57.
    J. Šimůnek, M.T. van Genuchten, M. Šejna, Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zo. J. 7, 587 (2008). Scholar
  58. 58.
    I. Sobol’, Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math. Comput. Simul. 55, 271–280 (2001). Scholar
  59. 59.
    M. Turco, R. Kodešová, G. Brunetti, A. Nikodem, M. Fér, P. Piro, Unsaturated hydraulic behaviour of a permeable pavement: laboratory investigation and numerical analysis by using the HYDRUS-2D model. J. Hydrol. 554, 780–791 (2017). Scholar
  60. 60.
    UMS GmbH, UMS (2015): Manual HYPROP, Version 2015-01 (2015)Google Scholar
  61. 61.
    W. Usher, Xantares, D. Hadka, bernardoct, Fernando, J. Herman, C. Mutel, SALib: New documentation, doc strings and installation requirements (2015).
  62. 62.
    M.T. van Genuchten, A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892 (1980). Scholar
  63. 63.
    M.T. Van Genuchten, P.J. Wierenga, Mass transfer studies in sorbing porous media I. Analytical solutions. Soil Sci. Soc. Am. J. 40, 473–480 (1976). Scholar
  64. 64.
    J.E. Warren, P.J. Root, The behavior of naturally fractured reservoirs. Soc. Pet. Eng. J. 3, 245–255 (1963). Scholar
  65. 65.
    T.H.F. Wong, T.D. Fletcher, H.P. Duncan, G.A. Jenkins, Modelling urban stormwater treatment—a unified approach. Ecol. Eng. 27, 58–70 (2006). Scholar
  66. 66.
    M. Wooldridge, An Introduction to MultiAgent Systems, 2nd edn. (Wiley, 2009), ISBN-10 0470519460, ISBN-13 978-0470519462Google Scholar
  67. 67.
    M. Zambrano-Bigiarini, R. Rojas, A model-independent Particle Swarm Optimisation software for model calibration. Environ. Model Softw. 43, 5–25 (2013). Scholar
  68. 68.
    S. Zhang, Y. Guo, Analytical probabilistic model for evaluating the hydrologic performance of green roofs. J. Hydrol. Eng. 18, 19–28 (2013). Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Patrizia Piro
    • 1
  • Michele Turco
    • 1
    Email author
  • Stefania Anna Palermo
    • 1
  • Francesca Principato
    • 1
  • Giuseppe Brunetti
    • 1
  1. 1.Department of Civil EngineeringUniversity of CalabriaRendeItaly

Personalised recommendations