Water Resources Management

, Volume 33, Issue 5, pp 1753–1768 | Cite as

Analyzing the Impact of Impervious Area Disconnection on Urban Runoff Control Using an Analytical Probabilistic Model

  • Jun WangEmail author
  • Shouhong ZhangEmail author
  • Yiping Guo


The rapid spreading of impervious areas has been a growing concern in urban stormwater management. Runoff originating from impervious areas directly connected to or disconnected from drainage systems contributes differently to the outflow at the downstream outlet. Extensive implementations of best management practices (BMPs) and low impact development (LID) practices necessitate more accurate quantifications of the runoff control effects of disconnecting impervious areas from drainage networks. An analytical probabilistic model was developed in this study that considers the differences between directly-connected and disconnected impervious areas. The novel feature of this model is that it can not only explicitly consider the effect of impervious area disconnection but also analytically calculate the runoff reduction effects contributed by impervious area disconnection. Model validity is demonstrated by comparing its outcomes with the results of a series of continuous simulations for cases with different types of soils and various land use parameters in Jackson, Mississippi and Billings, Montana, USA. Example applications of the proposed analytical model also demonstrate its usefulness in the planning and design of impervious area disconnections.


Impervious area disconnection Runoff reduction Analytical probabilistic model SWMM Urban catchment 



This work has been supported by the Fundamental Research Funds for the Central Universities (2016ZCQ06 and 2015ZCQ-SB-01), the National Natural Science Foundation of China (51609004), the Major Science and Technology Program for Water Pollution Control and Treatment (2017ZX07102-001), and the China Scholarship Council (201406220156). The editorial assistance provided by Mr. Robert Rawlins from McMaster University is greatly appreciated. The authors also thank the anonymous reviewers for their helpfulcomments.

Compliance with Ethical Standards

Conflict of Interest

The authors declare no conflict of interest.


  1. Adams BJ, Papa F (2000) Urban Stormwater management planning with analytical probabilistic models. Wiley, New YorkGoogle Scholar
  2. Alley WM, Veenhuis JE (1983) Effective impervious area in urban runoff modeling. J Hydraul Eng 109(2):313–319CrossRefGoogle Scholar
  3. Arnold CL, Gibbons CJ (1996) Impervious surface coverage: the emergence of a key environmental indicator. J Am Plan Assoc 62(2):243–258CrossRefGoogle Scholar
  4. Bacchi B, Balistrocchi M, Grossi G (2008) Proposal of a semi-probabilistic approach for storage facility design. Urban Water J 5(3):195–208CrossRefGoogle Scholar
  5. Balistrocchi M, Bacchi B (2011) Modelling the statistical dependence of rainfall event variables through copula functions. Hydrol Earth Syst Sci 15:1959–1977CrossRefGoogle Scholar
  6. Balistrocchi M, Grossi G, Bacchi B (2009) An analytical probabilistic model of the quality efficiency of a sewer tank. Water Resour Res 45:W12420. CrossRefGoogle Scholar
  7. Boulos PF (2017) Smart water network modeling for sustainable and resilient infrastructure. Water Resour Manag 31(10):3177–3188CrossRefGoogle Scholar
  8. Boyd MJ, Bufill MC, Knee RM (1993) Pervious and impervious runoff in urban catchments. Hydrol Sci J 38:463–478CrossRefGoogle Scholar
  9. Brabec E, Schulte S, Richards PL (2002) Impervious surfaces and water quality: a review of current literature and its implications for watershed planning. J Plan Lit 16(4):499–514CrossRefGoogle Scholar
  10. Cano OM, Barkdoll BD (2016) Multiobjective, socioeconomic, boundary-emanating, nearest distance algorithm for stormwater low-impact BMP selection and placement. J Water Resour Plan Manag 143(1):05016013. CrossRefGoogle Scholar
  11. Eagleson PS (1972) Dynamics of flood frequency. Water Resour Res 8(4):878–898CrossRefGoogle Scholar
  12. Ebrahimian A, Wilson BN, Gulliver JS (2016) Improved methods to estimate the effective impervious area in urban catchments using rainfall-runoff data. J Hydrol 536:109–118CrossRefGoogle Scholar
  13. Guo Y, Adams BJ (1998) Hydrologic analysis of urban catchments with event-based probabilistic models. Part I: runoff volume. Water Resour Res 34(12):3421–3431CrossRefGoogle Scholar
  14. Guo Y, Baetz BW (2007) Sizing of rainwater storage units for green building applications. J Hydrol Eng 12(2):197–205CrossRefGoogle Scholar
  15. Guo Y, Zhang S, Liu S (2014) Runoff reduction capabilities and irrigation requirements of green roofs. Water Resour Manag 28(5):1363–1378CrossRefGoogle Scholar
  16. Guo R, Guo Y, Wang J (2018) Stormwater capture and antecedent moisture characteristics of permeable pavements. Hydrol Process 32(17):2708–2720CrossRefGoogle Scholar
  17. Han W, Burian S (2009) Determining effective impervious area for urban hydrologic modeling. J Hydrol Eng 14:111–120CrossRefGoogle Scholar
  18. Hassini S, Guo Y (2016) Exponentiality test procedures for large samples of rainfall event characteristics. J Hydrol Eng 21(4):04016003. CrossRefGoogle Scholar
  19. Jefferson AJ, Bhaskar AS, Hopkins KG, Fanelli R, Avellaneda PM, McMillan SK (2017) Stormwater management network effectiveness and implications for urban watershed function: a critical review. Hydrol Process 31(23):4056–4080CrossRefGoogle Scholar
  20. Jing X, Zhang S, Zhang J, Wang Y, Wang Y (2017) Assessing efficiency and economic viability of rainwater harvesting systems for meeting non-potable water demands in four climatic zones of China. Resour Conserv Recycl 126:74–85CrossRefGoogle Scholar
  21. Jones JE, Earles TA, Fassman EA, Herricks EE, Urbonas B, Clary JK (2005) Urban storm-water regulations—are impervious area limits a good idea? J Environ Eng 131:176–179CrossRefGoogle Scholar
  22. Justel A, Peña D, Zamar R (1997) A multivariate Kolmogorov–Smirnov test of goodness of fit. Stat Probab Lett 35(3):251–259CrossRefGoogle Scholar
  23. Klein R (1979) Urbanization and stream quality impairment. Water Resour Bull 15(4):948–963CrossRefGoogle Scholar
  24. Lee JG, Heaney JP (2003) Estimation of urban imperviousness and its impacts on storm water systems. J Water Resour Plan Manag 129(5):419–426CrossRefGoogle Scholar
  25. Liu A, Goonetilleke A, Egodawatta P (2012) Inadequacy of land use and impervious area fraction for determining urban stormwater quality. Water Resour Manag 26:2259–2265CrossRefGoogle Scholar
  26. Miller JD, Hess T (2017) Urbanisation impacts on storm runoff along a rural-urban gradient. J Hydrol 552:474–489CrossRefGoogle Scholar
  27. Mueller GD, Thompson AM (2009) The ability of urban residential lawns to disconnect impervious area from municipal sewer systems. J Am Water Resour Assoc 45(5):1116–1126CrossRefGoogle Scholar
  28. National Research Council (2008) Urban stormwater in the United States. National Academies Press, Washington, DC Google Scholar
  29. Pielke RA (2005) Land use and climate change. Science 310(5754):1625–1626CrossRefGoogle Scholar
  30. Rossman LA (2015) Storm water management model User’s manual version 5.1. Cincinnati OH. Environmental Protection Agency, USAGoogle Scholar
  31. Roy AH, Shuster WD (2009) Assessing impervious surface connectivity and applications for watershed management. J Am Water Resour Assoc 45(1):198–209CrossRefGoogle Scholar
  32. Seo Y, Choi NJ, Schmidt AR (2013) Contribution of directly connected and isolated impervious areas to urban drainage network hydrographs. Hydrol Earth Syst Sci 17:3473–3483CrossRefGoogle Scholar
  33. Wang J, Guo Y (2018) An analytical stochastic approach for evaluating the performance of combined sewer overflow tanks. Water Resour Res 54(5):3357–3375CrossRefGoogle Scholar
  34. Wanielista MP, Yousef YA (1993) Stormwater management. Wiley, New YorkGoogle Scholar
  35. Yao L, Chen L, Wei W (2016) Assessing the effectiveness of imperviousness on stormwater runoff in micro urban catchments by model simulation. Hydrol Process 30(12):1836–1848CrossRefGoogle Scholar
  36. Zhang S, Guo Y (2013) Explicit equation for estimating the stormwater capture efficiency of rain gardens. J Hydrol Eng 18(12):1739–1748CrossRefGoogle Scholar
  37. Zhang S, Guo Y (2014) Stormwater capture efficiency of bioretention systems. Water Resour Manag 28(1):149–168CrossRefGoogle Scholar
  38. Zhang S, Zhang J, Jing X, Wang Y, Wang Y, Yue T (2018) Water saving efficiency and reliability of rainwater harvesting systems in the context of climate change. J Clean Prod 196:1341–1355CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Civil EngineeringMcMaster UniversityHamiltonCanada
  2. 2.School of Soil and Water ConservationBeijing Forestry UniversityBeijingChina

Personalised recommendations