Abstract
The drainage network always needs to adapt to environmental and climatic conditions to provide best quality services. Rehabilitation combining pipes substitution and storm tanks installation appears to be a good solution to overcome this problem. Unfortunately, the calculation time of such a rehabilitation scenario is too elevated for single-objective and multi-objective optimization. In this study, a methodology composed by search space reduction methodology whose purpose is to decrease the number of decision variables of the problem to solve and a multi-objective optimization whose purpose is to optimize the rehabilitation process and represent Pareto fronts as the result of urban drainage networks optimization is proposed. A comparison between different model results for multi-objective optimization is made. To obtain these results, Storm Water Management Model (SWMM) is first connected to a Pseudo Genetic Algorithm (PGA) for the search space reduction and then to a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. Pareto fronts are designed for investment costs instead of flood damage costs. The methodology is applied to a real network in the city of Medellin in Colombia. The results show that search space reduction methodology provides models with a considerably reduced number of decision variables. The multi-objective optimization shows that the models’ results used after the search space reduction obtain better outcomes than in the complete model in terms of calculation time and optimality of the solutions.
Highlights
Urban drainage networks experience failures in their operation due to aging and other structural problems, and due to urbanization and climate change, which is is affecting the intensities and frequencies of extreme rainfall events
The parameters considered in this process are defined as:
One approach considers that these networks should be adapted to the Extreme rainfall events and urbanization cause flooding problems to some originally well-designed drainage networks
Summary
Urban drainage networks experience failures in their operation due to aging and other structural problems, and due to urbanization and climate change, which is is affecting the intensities and frequencies of extreme rainfall events. Szewranski et al [3] developed a pluvial flood risk assessment tool to support stakeholders in rainwater management and adapt existing networks to climate change. Their tool implements spatial identification of flooding vulnerable areas and can be used in areas with different sizes. The involvement of people and communities in the urban vulnerability management leads to adequate solutions in adaptation to climate change These studies clearly show that adaptation is an important process to overcome the problem such as floods caused by extreme rainfall events
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