Development of a risk-based optimization approach to improve the performance of urban drainage systems

Abstract

ABSTRACT Considering the great deal of rainfall uncertainty in urban drainage system (UDS) design/rehabilitation, a copula-based design approach is developed within a Monte Carlo simulation (MCS) to improve system performance. Firstly, inundation zones are determined using HEC-RAS 2D and GIS tools. Then, inundation zones of flood scenarios are integrated with damage–depth functions in GIS to obtain the associated damage costs. Accordingly, a mapping is made between the flood volume (calculated by EPA-SWMM) and its related damage. This information is used in a coupled EPA-SWMM and differential evolution (DE) search algorithm to determine the best rehabilitation strategies. The approach is applied to a catchment in Tehran and its results are compared with the return-period method. Results show that the risk-based design approach could provide a 92% reduction in expected annual flood damage (EAD) and presents optimal designs with benefit-to-cost ratios up to 11, according to budget level. This approach yields more robust designs/strategies relative to the return-period method.