The management of urban surface water flood risks: SUDS performance in flood reduction from extreme events

2013 ◽  
Vol 67 (1) ◽  
pp. 99-108 ◽  
Author(s):  
C. Viavattene ◽  
J. B. Ellis

The need to improve the urban drainage network to meet recent urban growth and the redevelopment of old industrial and commercial areas provides an opportunity for managing urban surface water infrastructure in a more sustainable way. The use of sustainable urban drainage systems (SUDS) can reduce urban surface water flooding as well as the pollution impact of urban discharges on receiving waters. However, these techniques are not yet well known by many stakeholders involved in the decision-making process, or at least the evidence of their performance effectiveness may be doubted compared with more traditional engineering solutions often promoted by existing 1D/2D drainage models. The use of geographic information systems (GIS) in facilitating the inter-related risk analysis of sewer surface water overflows and urban flooding as well as in better communication with stakeholders is demonstrated in this paper. An innovative coupled 1D/2D urban sewer/overland flow model has been developed and tested in conjunction with a SUDS selection and location tool (SUDSLOC) to enable a robust management approach to surface water flood risks and to improve the resilience of the urban drainage infrastructure. The paper demonstrates the numerical and modelling basis of the integrated 1D/2D and SUDSLOC approach and the working assumptions and flexibility of the application together with some limitations and uncertainties. The role of the SUDSLOC modelling component in quantifying flow, and surcharge reduction benefits arising from the strategic selection and location of differing SUDS controls are also demonstrated for an extreme storm event scenario.

2019 ◽  
Vol 17 (7) ◽  
pp. 598-608 ◽  
Author(s):  
J. L. Webber ◽  
T. D. Fletcher ◽  
L. Cunningham ◽  
G. Fu ◽  
D. Butler ◽  
...  

2020 ◽  
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances 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.


2021 ◽  
Vol 25 (5) ◽  
pp. 2843-2860
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses, are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances, 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.


2021 ◽  
pp. 126125
Author(s):  
Chandra Prasad Ghimire ◽  
Willemijn M. Appels ◽  
Laura Grundy ◽  
Willis Ritchie ◽  
Stuart Bradley ◽  
...  

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