Literature DB >> 30029343

Optimizing surface and contributing areas of bioretention cells for stormwater runoff quality and quantity management.

Yang Yang1, Ting Fong May Chui2.   

Abstract

Bioretention cells (BCs) have received increasing attention in stormwater quality and quantity management. Selecting a suitable implementation level of BCs to concurrently achieve multiple performance targets (e.g., first flush reduction, peak flow reduction, and runoff volume reduction) is essential and often challenging. This study proposes a method for formulating suitable sizing criteria for multi-objective stormwater management. The performance of BCs of different areas is assessed first using the Storm Water Management Model (SWMM) and then look-up curves (i.e., the performance target versus the required area of BCs) for each of the performance targets and the multi-objective cases are derived. In some cases, the available area of BCs is limited; to account for the multi-objective management interests and maximize the system-wide benefits, an optimal contributing drainage area for BCs should be selected. A method is therefore developed to solve this optimization problem. A case study of Hong Kong shows that the required area of BCs increases non-linearly with increased performance targets. With a limited area of BCs, larger contributing areas are favorable if no special emphasis is placed on the intensive control of peak flow reduction. Design standards (e.g., the intensity of the design storm), evaluation methods (e.g., depth threshold of the initial portion of runoff), and management preference all exert some influence on the resultant sizing criteria and optimization results. Carefully selecting these catchment-specific evaluation methods should lead to more appropriate sizing criteria and thus promote more efficient BC adoption.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bioretention cell; Low impact development; Optimization; SWMM; Sizing; Sustainable drainage system

Mesh:

Year:  2017        PMID: 30029343     DOI: 10.1016/j.jenvman.2017.11.064

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model.

Authors:  Dongwei Qiu; Hao Xu; Dean Luo; Qing Ye; Shaofu Li; Tong Wang; Keliang Ding
Journal:  PLoS One       Date:  2020-01-21       Impact factor: 3.240

  1 in total

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