Abstract
This study examined the influence of spatial resolution on model parameterization, output, and the parameter transferability between different resolutions using the Storm Water Management Model. High-resolution models, in which most subcatchments were homogeneous, and high-resolution-based low-resolution models (in 3 scenarios) were constructed for a highly urbanized catchment in Beijing. The results indicated that the parameterization and simulation results were affected by both spatial resolution and rainfall characteristics. The simulated peak inflow and total runoff volume were sensitive to the spatial resolution, but did not show a consistent tendency. High-resolution models performed very well for both calibration and validation events in terms of three indexes: 1) the Nash-Sutcliffe efficiency, 2) the peak flow error, and 3) the volume error; indication of the advantage of using these models. The parameters obtained from high-resolution models could be directly used in the low-resolution models and performed well in the simulation of heavy rain and torrential rain and in the study area where sub-area routing is insignificant. Alternatively, sub-area routing should be considered and estimated approximately. The successful scale conversion from high spatial resolution to low spatial resolution is of great significance for the hydrological simulation of ungauged large areas.
Similar content being viewed by others
References
Baek S S, Choi D H, Jung J W, Lee H J, Lee H, Yoon K S, Cho K H (2015). Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: experimental and modeling approach. Water Res, 86: 122–131
Barco J, Wong K M, Stenstrom MK (2008). Automatic calibration of the U.S. EPA SWMM model for a large urban catchment. J Hydraul Eng, 134(4): 466–474
Bedient P B, Huber W C (2002). Hydrology and Flood Plain Analysis. New Jersey: Prentice-Hall
Blöschl G, Sivapalan M (1995). Scale issues in hydrological modelling: a review. Hydrol Processes, 9(3–4): 251–290
Borris M, Viklander M, Gustafsson A M, Marsalek J (2014). Modelling the effects of changes in rainfall event characteristics on TSS loads in urban runoff. Hydrol Processes, 28(4): 1787–1796
Chen A S, Evans B, Djordjević S, Savić D A (2012). A coarse-grid approach to representing building blockage effects in 2D urban flood modelling. J Hydrol (Amst), 426–427(6): 1–16
Chow M F, Yusop Z, Toriman M E (2012). Modelling runoff quantity and quality in tropical urban catchments using storm water management model. Int J Environ Sci Technol, 9(4): 737–748
di Pierro F, Khu S T, Savi D (2006). From single-objective to multipleobjective multiple-rainfall events automatic calibration of urban storm water runoff models using genetic algorithms. Water Sci Technol, 54(6–7): 57–64
Elliott A H, Trowsdale S A, Wadhwa S (2009). Effect of aggregation of on-site storm-water control devices in an urban catchment model. J Hydrol Eng, 14(9): 975–983
Ghosh I, Hellweger F L (2012). Effects of spatial resolution in urban hydrologic simulations. J Hydrol Eng, 17(1): 129–137
Gooré Bi E, Monette F, Gachon P, Gaspéri J, Perrodin Y (2015). Quantitative and qualitative assessment of the impact of climate change on a combined sewer overflow and its receiving water body. Environ Sci Pollut Res Int, 22(15): 11905–11921
Huber W C, Dickinson R E, Barnwell T O Jr, Branch A (1988). Storm water management model; version 4. Environmental Protection Agency, United States
James W, Huber W, Dickinson R, Pitt R, Roesner L, Aldrich J (2003). User’s Guide to PCSWMM. Computational Hydraulics International: Guelph, Ontario, Canada
Knighton J, White E, Lennon E, Rajan R (2014). Development of probability distributions for urban hydrologicmodel parameters and a Monte Carlo analysis of model sensitivity. Hydrol Processes, 28(19): 5131–5139
Krebs G, Kokkonen T, Valtanen M, Koivusalo H, Setälä H (2013). A high resolution application of a stormwater management model (SWMM) using genetic parameter optimization. Urban Water J, 10 (6): 394–410
Krebs G, Kokkonen T, Valtanen M, Setälä H, Koivusalo H (2014). Spatial resolution considerations for urban hydrological modelling. J Hydrol (Amst), 512: 482–497
Leandro J, Schumann A, Pfister A (2016). A step towards considering the spatial heterogeneity of urban key features in urban hydrology flood modelling. J Hydrol (Amst), 535: 356–365
Liong S Y, Chan W T, Lum L H (1991). Knowledge-based system for SWMM runoff component calibration. J Water Resour Plan Manage, 117(5): 507–524
Madsen H (2003). Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives. Adv Water Resour, 26(2): 205–216
Melsen L, Teuling A, Torfs P, Zappa M, Mizukami N, Clark M, Uijlenhoet R (2016). Representation of spatial and temporal variability in large-domain hydrological models: case study for a mesoscale pre-alpine basin. Hydrol Earth Syst Sci Discuss, 20: 1–38
Palla A, Gnecco I (2015). Hydrologic modeling of low impact development systems at the urban catchment scale. J Hydrol (Amst), 528: 361–368
Park S Y, Lee K W, Park I H, Ha S R (2008). Effect of the aggregation level of surface runoff fields and sewer network for a SWMM simulation. Desalination, 226(1–3): 328–337
Peel M C, Blöschl G (2011). Hydrological modelling in a changing world. Prog Phys Geogr, 35(2): 249–261
Peterson E W, Wicks C M (2006). Assessing the importance of conduit geometry and physical parameters in karst systems using the storm water management model (SWMM). J Hydrol (Amst), 329(1‒2): 294–305
Ritter A, Muñoz-Carpena R (2013). Performance evaluation of hydrological models: statistical significance for reducing subjectivity in goodness-of-fit assessments. J Hydrol (Amst), 480: 33–45
Rosa D J, Clausen J C, Dietz M E (2015). Calibration and verification of SWMM for low impact development. J Am Water Resour Assoc, 51 (3): 746–757
Rossman L A (2010). Storm water management model user’s manual, version 5.0. National Risk Management Research Laboratory, Office of Research and Development, US Environmental Protection Agency
Shen Z Y, Chen L, Liao Q, Liu R M, Huang Q (2013). A comprehensive study of the effect of GIS data on hydrology and non-point source pollution modeling. Agric Water Manage, 118: 93–102
Shen Z, Hou X, Li W, Aini G (2014). Relating landscape characteristics to non-point source pollution in a typical urbanized watershed in the municipality of Beijing. Landsc Urban Plan, 123: 96–107
Sun N, Hall M, Hong B, Zhang L (2014). Impact of SWMM catchment discretization: case study in Syracuse, New York. J Hydrol Eng, 19 (1): 223–234
Tian Y, Zheng Y, Wu B, Wu X, Liu L, Zheng C (2015). Modeling surface water-groundwater interaction in arid and semi-arid regions with intensive agriculture. Environ Model Softw, 63: 170–184
Tsihrintzis V A, Hamid R (1998). Runoff quality prediction from small urban catchments using SWMM. Hydrol Processes, 12(2): 311–329
Vaze J, Chiew F H (2003). Comparative evaluation of urban storm water quality models. Water Resour Res, 39(10): 1280
Vojinovic Z, Tutulic D (2009). On the use of 1D and coupled 1D-2D modelling approaches for assessment of flood damage in urban areas. Urban Water J, 6(3): 183–199
Wang K H, Altunkaynak A (2012). Comparative case study of rainfallrunoff modeling betweenSWMMand fuzzy logic approach. J Hydrol Eng, 17(2): 283–291
Zaghloul N A (1981). SWMM model and level of discretization. J Hydraul Div, 107(11): 1535–1545
Zhang Y, Vaze J, Chiew F H, Teng J, Li M (2014). Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling. J Hydrol (Amst), 517: 936–948
Zhao D Q, Chen J N, Wang H Z, Tong O Y, Chao S B, Sheng Z (2009). GIS-based urban rainfall-runoff modeling using an automatic catchment-discretization approach: a case study in Macau. Environ Earth Sci, 59(2): 465–472
Acknowledgements
This project was supported by the State Key Program of the National Natural Science Foundation of China (Grant No. 41530635), the Fund for Innovative Research Group of the National Natural Science Foundation of China (Grant No. 51421065), Open Research Fund Program of Key Laboratory of Urban Storm Water System and Water Environment, Ministry of Education.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hou, X., Chen, L., Liu, X. et al. Parameter transferability across spatial resolutions in urban hydrological modelling: a case study in Beijing, China. Front. Earth Sci. 13, 18–32 (2019). https://doi.org/10.1007/s11707-018-0710-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11707-018-0710-3