A NOVEL VOLUME OPTIMIZATION METHOD FOR DETENTION TANKS FOR FLOODING IMMIGRATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHM

With the rapid development of urbanization, the impervious area increased markedly. The detention tank is one of the important measures to alleviate urban flooding. However, the application of detention tanks faces many problems, such as the unreasonable design method, and a lack of lost-benefit analysis. A novel optimization method of the detention tank based on the coupling of InfoWorks ICM and the multi-objective genetic algorithm was proposed. Taking an urban area as an example, the waterlogging area and detention volume were analyzed by InfoWorks ICM. The total overflow volume of ponding points in the area was 14355 m³, 17102 m³ and 19838 m³ under the 5-year,10-year and 20-year return periods of rainfall. Coupled the above results with the multi-objective genetic algorithm, with the reduction of project cost and waterlogging risk as the objective function, and with the floor area and efficiency index of the reservoir as the constraint condition, five optimization schemes were proposed. By comparing the distribution characteristics of the optimal solution under 5-year, 10-year,20-year rainfall return periods, scheme 2 was determined as the optimal scheme, and the corresponding construction cost of the storage tanks was 2713, 4612, 62.4 million yuan. Therefore, the method of coupling the InfoWorks ICM model with genetic algorithm can be used to optimize the scale of urban waterlogging storage ponds.