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To minimize the change of hydrological regime due to urbanization, stormwater best management practices have been enforced in the past few decades in certain urban areas. One approach is to implement small-scale hydrologic controls, such as bio-retention systems, throughout a catchment. 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. Thus, the choices and components of hydrological models are usually restricted. 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 able to utilize results of any hydrological model, allowing users to simulate processes that are most relevant to their studies. The GA is written in Fortran considering factors such as topography, distance from the 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.


Session R36, Modeling of Urban Flooding II



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