Abstract
Urban flooding is a reoccurring disaster, and its frequency and intensity are likely to increase in the future due to the increasing frequency of storm events. Up-to-date monitoring on the distribution of flood hazards in cities is necessary and valuable for urban planning. This research combines two common urban flooding approaches, namely hydraulic and GIS models, in a case study of London, Ontario, Canada. The hydraulic–GIS combined model employs the hydraulic concept in a simplified GIS frame, hence avoiding heavy computation in the hydraulic model and arbitrary coefficients in a GIS model. We used a binary logistic regression model to integrate the hydraulic concept in a GIS model. The multi-criteria GIS model built by binary logistic regression was able to simulate the results from the hydraulic model with good consistency. Such a strategy serves as a promising prototype for addressing similar geographical modelling issues, where the time-consuming physical model can be potentially replaced by a simplified GIS model. Furthermore, the impervious surface percentage is an important input in the hydraulic model. This research experimented different impervious surface percentages as input to the hydraulic model and found that a spatially variable impervious surface percentage achieves better agreement with hydraulic modelling than that of uniform (25% and 42%) impervious surface percentages.
Similar content being viewed by others
References
Alfieri L, Salamon P, Bianchi A, Neal J, Bates P, Feyen L (2014) Advances in pan-European flood hazard mapping. Hydrol Process 28(13):4067–4077
Ashley RM, Balmforth DJ, Saul AJ, Blanskby JD (2005) Flooding in the future–predicting climate change, risks and responses in urban areas. Water Sci Technol 52(5):265–273
Brunner GW (1995) HEC-RAS river analysis system. Hydraulic reference manual, version 1.0. Hydrologic Engineering Center Davis, CA
Center, Hydrologic Engineering (2001) The hydrologic modeling system (HEC-HMS). US Army Corps of Engineers, Hydrologic Engineering Center, Davis
Chen J, Hill AA, Urbano LD (2009) A GIS-based model for urban flood inundation. J Hydrol 373(1–2):184–192
Chen Y, Zhou H, Zhang H, Guoming D, Zhou J (2015) Urban flood risk warning under rapid urbanization. Environ Res 139:3–10
Cook A, Merwade V (2009) Effect of topographic data, geometric configuration and modeling approach on flood inundation mapping. J Hydrol 377(1–2):131–142
Di Baldassarre G, Guy Schumann G, Bates PD, Freer JE, Beven KJ (2010) Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches. Hydrol Sci J J Sci Hydrol 55(3):364–376
Easterling DR, Evans JL, Ya Groisman P, Karl TR, Kunkel KE, Ambenje P (2000) Observed variability and trends in extreme climate events: a brief review. Bull Am Meteorol Soc 81(3):417–426
Elvidge CD, Tuttle BT, Sutton PC, Baugh KE, Howard AT, Milesi C, Bhaduri B, Nemani R (2007) Global distribution and density of constructed impervious surfaces. Sensors 7(9):1962–1979
EPA, US (2015) Storm water management model (SWMM). https://www.epa.gov/waterresearch/storm-water-management-model-swmm. Accessed 17 Mar 2017
Frank E, Ostan A, Coccato M, Stelling GS (2001) Use of an integrated one dimensional-two dimensional hydraulic modelling approach for flood hazard and risk mapping. WIT Trans Ecol Environ 50:99–108
Gall M, Boruff BJ, Cutter SL (2007) Assessing flood hazard zones in the absence of digital floodplain maps: comparison of alternative approaches. Nat Hazards Rev 8(1):1–12
Galland J-C, Goutal N, Hervouet J-M (1991) TELEMAC: A new numerical model for solving shallow water equations. Adv Water Resour 14(3):138–148
Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143(1):29–36
Hollis GE (1975) The effect of urbanization on floods of different recurrence interval. Water Resour Res 11(3):431–435
Kazakis N, Kougias I, Patsialis T (2015) Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. Sci Total Environ 538:555–563
Keifer CJ, Chu HH (1957) Synthetic storm pattern for drainage design. J Hydraul Div 83(4):1–25
Kreibich H, Piroth K, Seifert I, Maiwald H, Kunert U, Schwarz J, Thieken AH (2009) Is flow velocity a significant parameter in flood damage modelling? Nat Hazards Earth Syst Sci 9:1679–1692
Lemeshow S, Hosmer DW Jr. (1982) A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 115(1):92–106
Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, Hoboken
Nirupama N, Simonovic SP (2007) Increase of flood risk due to urbanisation: a canadian example. Nat Hazards 40(1):25
Ontario Ministry of Finance (2019) Ontario population projections, 2018–2046. Retrieved from ontario.ca/finance
Ouma YO, Tateishi R (2014) Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: methodological overview and case study assessment. Water 6(6):1515–1545
Pcswmm CHI (2016) http://www.chiwater.com/Software. PCSWMM/index. asp. Accessed 9 Sept 2015
Plackett RL (1983) Karl Pearson and the Chi-squared test. Int Stat Rev 51:59–72
Pradhan B (2010) Flood susceptible mapping and risk area delineation using logistic regression. GIS and remote sensing. J Spat Hydrol 9(2):1–18
Prisloe M, Giannotti L, Sleavin W (2000) Determining impervious surfaces for watershed modeling applications. In: Proceedings of the 8th national nonpoint source monitoring workshop
Rossman LA (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 Cincinnati, Cincinnati
Schreider SYu, Smith DI, Jakeman AJ (2000) Climate change impacts on urban flooding. Clim Change 47(1–2):91–115
Schumann G, Bates PD, Apel H, Aronica GT (2018) Global flood hazard mapping, modeling, and forecasting: challenges and perspectives. Glob Flood Hazard Appl Model Map Forecast 3:239–244
Shearman JO (1990) User’s manual for WSPRO, a computer model for water surface profile computations. Federal Highway Administration, Washington
Simonovic SP, Peck A (2009) Updated rainfall intensity duration frequency curves for the City of London under the changing climate. Department of Civil and Environmental Engineering, The University of Western Ontario, London
Smith BK, Smith JA, Baeck ML, Miller AJ (2015) Exploring storage and runoff generation processes for urban flooding through a physically based watershed model. Water Resour Res 51(3):1552–1569
UTRCA publication (1955) Brief on flood control measures for the Upper Thames Watershed
Villarini G, Smith JA, Serinaldi F, Bales J, Bates PD, Krajewski WF (2009) Flood frequency analysis for nonstationary annual peak records in an urban drainage basin. Adv Water Resour 32(8):1255–1266
Water M (2010) MUSIC guidelines; recommended input parameters and modelling approaches for MUSIC users. State Government of Victoria, Melbourne
Xu P-z, Jiang T, King L (2000) Hydrologic/hydraulic modelling and flood risk analysis for the West Tiaoxi Catchment, Taihu Lake Region, China. Chin Geogra Sci 10(4):309–318
Zerger A (2002) Examining GIS decision utility for natural hazard risk modelling. Environ Model Softw 17(3):287–294
Zhang S, Pan B (2014) An urban storm-inundation simulation method based on GIS. J Hydrol 517:260–268
Acknowledgement
This work was supported by both the NSERC Engage Grant awarded to Dr. Jinfei Wang with industry support from Esri Canada Limited and the NSERC Discovery Grant awarded to Dr. Jinfei Wang. This research used a free university license for the PCSWMM software. Funding was provided by NESRC Discovery (Grant No. RGPIN-2016-04741).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Feng, B., Wang, J., Zhang, Y. et al. Urban flood hazard mapping using a hydraulic–GIS combined model. Nat Hazards 100, 1089–1104 (2020). https://doi.org/10.1007/s11069-019-03850-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-019-03850-7