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

TitleOptimizing bio-retention system locations for stormwater management using genetic algorithm
Authors
Issue Date2014
Citation
The 11th International Conference on Hydroinformatics (HIC 2014), New York City, NY., 17-21 August 2014. In Conference Proceedings, 2014, p. 1-4 How to Cite?
AbstractAs 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.
Persistent Identifierhttp://hdl.handle.net/10722/199510

 

DC FieldValueLanguage
dc.contributor.authorTrinh, DHen_US
dc.contributor.authorChui, MTFen_US
dc.date.accessioned2014-07-22T01:21:06Z-
dc.date.available2014-07-22T01:21:06Z-
dc.date.issued2014-
dc.identifier.citationThe 11th International Conference on Hydroinformatics (HIC 2014), New York City, NY., 17-21 August 2014. In Conference Proceedings, 2014, p. 1-4en_US
dc.identifier.urihttp://hdl.handle.net/10722/199510-
dc.description.abstractAs 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.-
dc.languageengen_US
dc.relation.ispartof11th International Conference on Hydroinformatics Proceedingsen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleOptimizing bio-retention system locations for stormwater management using genetic algorithmen_US
dc.typeConference_Paperen_US
dc.identifier.emailChui, MTF: maychui@hku.hken_US
dc.identifier.authorityChui, MTF=rp01696en_US
dc.description.naturepostprint-
dc.identifier.hkuros231022en_US
dc.identifier.spage1-
dc.identifier.epage4-
dc.customcontrol.immutablesml 140820-

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