Otimização multiobjetivo de bacias de detenção em sistemas de drenagem urbana utilizando algoritmos genéticos

Abstract

The excessive waterproofing of the soil, as a consequence of urbanization, leads to a substantial increase in runoff, which places large cities in situations of frequent vulnerability to the occurrence of floods. To deal with this problem, adaptations to the urban drainage system are becoming increasingly necessary. Among these changes, the implementation of detention basins proves to be an efficient solution by temporarily storing rainwater and reducing peak flows in areas with already consolidated occupation. However, proposing a system of detentions that reduces the volume of flooding as the solution is the one with the lowest financial cost, involves different criteria and complex decisions, often impracticable to be obtained through traditional methods of trial and error. The optimization models, more specifically multiobjective optimization models, jointly with the hydrological simulation models, appear as an interesting tool in the search for optimal solutions that meet multiple conflicting objectives. Thus, the present study aimed to test the integration between a genetic algorithm and the SWMM hydrological simulation model to optimize the location and dimensions of a set of detention basins, aiming to simultaneously minimize the total flood volume (VTI) and the total detention volume (VTD), considering that the detention volume will reflect the costs involved in implementing the storage structure. To this, 8 cases were proposed to analyze the interference of incorporating different restrictions and decision variables, to obtain a more complete optimization model to assist decision-makers. The model was applied to an urban area located in Brasília and evaluated for three levels of efficiency in reducing the flood volume (30 %, 60 %, and 90 %). The results indicated that incorporating the variable corresponding to the location of the detentions provided Pareto Fronts with better solutions in terms of efficiency in reducing floods. It was also possible to realize that there are key points for the implementation of detentions, capable of further reducing the VTI. This was also noticed when incorporating the restriction of a maximum outlet flow in the drainage system's outlet, which imposed on the solutions the necessity for storage structures with smaller outlet diameters in downstream points to the network. In general, the study presented consistent optimal solutions that when evaluated individually showed advantages in the integration between optimization and hydrological modeling.