A Decision Support Model for the Optimal Siting and Sizing of Storage Units in Stormwater Drainage Systems

A Decision Support Model for the Optimal Siting and Sizing of Storage Units in Stormwater Drainage Systems

M.C. Cunha J.A. Zeferino N.E. Simões G.I. Santos J.G. Saldarriaga

MARE, Department of Civil Engineering, University of Coimbra, Portugal.

Department of Civil Engineering, University of Coimbra, Portugal.

CIACUA, Aqueduct and Sewage Research Center, Department of Civil and Environmental Engineering, University of Los Andes, Colombia

1 February 2017
| Citation



Climate change and urbanization are the main factors involved in increasing cities’ susceptibility to flood events. Extreme rainfall events are occurring more often due to climate change and this, together with the effect of impermeable surfaces, means that the runoff increases. Consequently, the existing stormwater drainage systems need to be adapted. One solution to adapt these systems would be to include infrastructure elements, such as storage units, in the hydraulic network to control flow and reduce peak flows.

This paper presents a decision support model for the optimal siting and sizing of storage units with flow control in existing urban stormwater systems where flood events are frequent. Direct flood damage will be taken into account in the decision process, and thus the cost of construction and maintenance of storage units will be considered along with the cost of flood damage, in the determination of the solution to be implemented. This damage relates to losses in the affected areas and depend on the land use type (e.g. uses of buildings) and on the flood depth affecting it.

A computer program, OptSU, was developed to implement the model. It includes a resolution method based on a simulated annealing algorithm that calls upon a hydraulic simulator whenever necessary. The optimization model is then tested on a case study inspired by a real urban stormwater system in Portugal.


detention basins, optimization, urban drainage, urban floods


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