COMPARISON BETWEEN SINGLE AND MULTI-OBJECTIVE STRATEGIES FOR URBAN DRAINAGE MODEL OPTIMIZATION USING GENETIC ALGORITHMS: A case study of Badalona Urban drainage network.

Urban flooding has become a worldwide catastrophic disaster including in Spain due to 
increased urbanization, reduced infiltration capacity, and climate change. Though the annual 
average rainfall is low in Badalona, a city located in eastern Catalonia and a part of the Barcelona 
metropolitan area, it experiences pluvial and flash floods due to the intense rainfall that occurred 
in a short interval of time brought by the Mediterranean climate. The combined sewer system of 
the drainage network in Badalona City acts as the conveyor of the urban sewer system, 
stormwater runoff, and industrial wastewater system. To minimize the surcharging of the 
drainage networks, it is necessary to predict the surface runoff and forecast the floods as 
accurately as possible. Drainage models such as MOUSE, Infor Works, and SWMM were 
developed for such applications for the city. However, the manual calibration results in a long and 
tedious process, primarily based on the educated guess of the modeler which could lead to a 
possibility of missing the optimum parameter sets during calibration. This makes an automatic 
process preferable. Additionally, the optimization done using multi-objective function strategies 
has been shown to provide more reliable results compared to the traditional methods. This 
project aimed to develop and compare the single and multi-objective function strategies to 
optimize the urban drainage model parameters using genetic algorithms. Upon the comparative 
analysis of single and multi-objective optimization strategies, it was demonstrated that the multi
objective optimization provides more robust and versatile model compared to single objective 
approach providing a balanced trade-off between the multiple objectives. This aids in providing 
a holistic approach for drainage network management of an area providing resiliency and 
efficiency through a robust framework for addressing various issues such as flood preventions, 
water quality management and model performance.