Articles | Volume 25, issue 5
Hydrol. Earth Syst. Sci., 25, 2843–2860, 2021
https://doi.org/10.5194/hess-25-2843-2021
Hydrol. Earth Syst. Sci., 25, 2843–2860, 2021
https://doi.org/10.5194/hess-25-2843-2021

Review article 27 May 2021

Review article | 27 May 2021

Urban surface water flood modelling – a comprehensive review of current models and future challenges

Kaihua Guo et al.

Related authors

Comparative analysis and implications of sustainable Flood Risk Management in four front-end countries: The United Kingdom, the Netherlands, the United States, & Japan
Faith Ka Shun Chan, Liang Emlyn Yang, Gordon Mitchell, Nigel Wright, Mingfu Guan, Xiaohui Lu, Zilin Wang, Burrell Montz, and Olalekan Adekola
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-268,https://doi.org/10.5194/nhess-2021-268, 2021
Preprint under review for NHESS
Short summary
Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach
Samuli Launiainen, Mingfu Guan, Aura Salmivaara, and Antti-Jussi Kieloaho
Hydrol. Earth Syst. Sci., 23, 3457–3480, https://doi.org/10.5194/hess-23-3457-2019,https://doi.org/10.5194/hess-23-3457-2019, 2019
Short summary
City-scale accessibility of emergency responders operating during flood events
Daniel Green, Dapeng Yu, Ian Pattison, Robert Wilby, Lee Bosher, Ramila Patel, Philip Thompson, Keith Trowell, Julia Draycon, Martin Halse, Lili Yang, and Tim Ryley
Nat. Hazards Earth Syst. Sci., 17, 1–16, https://doi.org/10.5194/nhess-17-1-2017,https://doi.org/10.5194/nhess-17-1-2017, 2017
Short summary
Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata
L. Liu, Y. Liu, X. Wang, D. Yu, K. Liu, H. Huang, and G. Hu
Nat. Hazards Earth Syst. Sci., 15, 381–391, https://doi.org/10.5194/nhess-15-381-2015,https://doi.org/10.5194/nhess-15-381-2015, 2015
Short summary
Rainfall and temperature estimation for a data sparse region
R. L. Wilby and D. Yu
Hydrol. Earth Syst. Sci., 17, 3937–3955, https://doi.org/10.5194/hess-17-3937-2013,https://doi.org/10.5194/hess-17-3937-2013, 2013

Related subject area

Subject: Urban Hydrology | Techniques and Approaches: Modelling approaches
The impact of the spatiotemporal structure of rainfall on flood frequency over a small urban watershed: an approach coupling stochastic storm transposition and hydrologic modeling
Zhengzheng Zhou, James A. Smith, Mary Lynn Baeck, Daniel B. Wright, Brianne K. Smith, and Shuguang Liu
Hydrol. Earth Syst. Sci., 25, 4701–4717, https://doi.org/10.5194/hess-25-4701-2021,https://doi.org/10.5194/hess-25-4701-2021, 2021
Short summary
Space variability impacts on hydrological responses of nature-based solutions and the resulting uncertainty: a case study of Guyancourt (France)
Yangzi Qiu, Igor da Silva Rocha Paz, Feihu Chen, Pierre-Antoine Versini, Daniel Schertzer, and Ioulia Tchiguirinskaia
Hydrol. Earth Syst. Sci., 25, 3137–3162, https://doi.org/10.5194/hess-25-3137-2021,https://doi.org/10.5194/hess-25-3137-2021, 2021
Short summary
Resampling and ensemble techniques for improving ANN-based high-flow forecast accuracy
Everett Snieder, Karen Abogadil, and Usman T. Khan
Hydrol. Earth Syst. Sci., 25, 2543–2566, https://doi.org/10.5194/hess-25-2543-2021,https://doi.org/10.5194/hess-25-2543-2021, 2021
Short summary
Evaluating different machine learning methods to simulate runoff from extensive green roofs
Elhadi Mohsen Hassan Abdalla, Vincent Pons, Virginia Stovin, Simon De-Ville, Elizabeth Fassman-Beck, Knut Alfredsen, and Tone Merete Muthanna
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-124,https://doi.org/10.5194/hess-2021-124, 2021
Revised manuscript accepted for HESS
Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods
Yang Yang and Ting Fong May Chui
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-460,https://doi.org/10.5194/hess-2020-460, 2020
Revised manuscript accepted for HESS
Short summary

Cited articles

Audusse, E., Bouchut, F. o., Bristeau, M.-O., Klein, R., and Perthame, B.: A Fast and Stable Well-Balanced Scheme with Hydrostatic Reconstruction for Shallow Water Flows, SIAM J. Sci. Comput., 25, 2050–2016, https://doi.org/10.1137/S1064827503431090, 2004. 
Austin, R. J., Chen, A. S., Savic, D. A., and Djordjevic, S.: Quick and accurate Cellular Automata sewer simulator, J. Hydroinform., 16, 1359–1374, https://doi.org/10.2166/hydro.2014.070, 2014. 
Barredo, J. I.: Normalised flood losses in Europe: 1970–2006, Nat. Hazards Earth Syst. Sci., 9, 97–104, https://doi.org/10.5194/nhess-9-97-2009, 2009. 
Barredo, J. I., Saurí, D., and Llasat, M. C.: Assessing trends in insured losses from floods in Spain 1971–2008, Nat. Hazards Earth Syst. Sci., 12, 1723–1729, https://doi.org/10.5194/nhess-12-1723-2012, 2012. 
Bates, P. D., Horritt, M. S., and Fewtrell, T. J.: A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling, J. Hydrol., 387, 33–45, https://doi.org/10.1016/j.jhydrol.2010.03.027, 2010. 
Short summary
This study presents a comprehensive review of models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. It explores the advantages and limitations of existing models and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.