Optimizing bio-retention system locations for stormwater management using genetic algorithm

Abstract

As part of stormwater best management practices, bio-retention systems have been applied in a number of developed countries to minimize the change of hydrological regime due to urbanization. Optimization techniques have also been applied to determine the locations that give the most hydrological benefits. However, optimization tools are commonly built in together with specific hydrological models, usually restricting the choices and components of hydrological models. Furthermore, it is redundant to build another hydrological model that has a built-in optimization tool if a hydrological model, and possibly more comprehensive one, has already been developed for the study area. The objective of this study is to develop a genetic algorithm (GA) that is independent from and can therefore be coupled with any existing integrated distributed hydrological model to optimize the locations of bio-retention systems. The GA is written in Visual Basic considering factors such as topography, distance from a river and groundwater table depth. The alternative combinations of bio-retention locations suggested by the GA are used as inputs of an integrated distributed hydrological model. The combination that gives the lowest outlet discharge is then regarded as the best solution. We demonstrate the approach by taking Marina catchment in Singapore as a case study and feeding the GA with results from MIKESHE. Overall, the GA developed is not only transferable to other study area but also can also be coupled with any hydrological model that is the most suitable for that particular case study.