SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: a case study in Tianjin

doi:10.1007/s11783-017-0934-6

Front. Environ. Sci. Eng.

2017, Vol. 11

Issue (4) : 1 https://doi.org/10.1007/s11783-017-0934-6

RESEARCH ARTICLE

SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: a case study in Tianjin

Te Xu, Haifeng Jia(

), Zheng Wang, Xuhui Mao, Changqing Xu

School of Environment, Tsinghua University, Beijing 100084, China

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Abstract

A SWMM-based methodology of block-scale LID-BMPs planning was developed.

LID-BMP chain layout optimization was combined with block-scale scenario analysis.

A strategy was devised to couple NSGA-II to SWMM.

Planning targets were satisfied in the case study in Tianjin.

Scenario evaluation and selection was robust with varied weight values.

Low impact development type of best management practices (LID-BMPs) aims to mitigate urban stormwater runoff and lessen pollutant loads in an economical and eco-friendly way and has become a global concern in modern urban stormwater management. A new methodology based on stormwater management model (SWMM) for block-scale LID-BMPs planning was developed. This method integrated LID-BMP chain layout optimization in site-scale parcels with scenario analysis in the entire block-scale urban area. Non-dominated sorting genetic algorithm (NSGA-II) was successfully coupled to SWMM through Python to complete the site-scale optimization process. Different LID scenarios of the research area were designed on the basis of the optimized LID-BMP chain layout. A multi-index evaluation that considered runoff quantity indices, pollutant loads, and construction costs simultaneously helped select the cost-effective scenario as the final planning scheme. A case study in Tianjin, China, was conducted to demonstrate the proposed methodology. Results showed that more than 75% control rate of total runoff volume, 22%–46% peak flow reduction efficiency, and more than 32% pollutant removal rate were achieved. The robustness analysis indicated that the selected final planning scheme was considerably robust with varied weight values.

Keywords Stormwater management LID-BMPs planning SWMM LID-BMP chain NSGA-II Scenario analysis

Corresponding Author(s): Haifeng Jia

Issue Date: 26 April 2017

Cite this article:

Te Xu,Haifeng Jia,Zheng Wang, et al. SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: a case study in Tianjin[J]. Front. Environ. Sci. Eng., 2017, 11(4): 1.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-017-0934-6
https://academic.hep.com.cn/fese/EN/Y2017/V11/I4/1

Fig.1 Research roadmap

Fig.2 Exploration of the research area and the basic planning information. (a) location of the study site, Tanggu Bay, a coastal urban area near Bohai Sea; (b) the land use plan and the delimitation of LID-BMPs planning; (c) the layout and components of the rainwater system, displayed in SWMM 5.1

Tab.1 Land use plan information

Fig.3 Designed LID-BMP chain. “50%” means that half of the roof runoff after treatment of RFB will directly enter into VS, and the other half will initially be combined with the runoff from impervious area and then be treated by PP. In China, road/pavement on the one side and green land on the other side of the building is a common phenomenon; thus, the “50%” simplification is reasonable. The area ratio of each LID-BMP facility (i.e., the white rectangle) is the decision variable in optimization

Fig.4 Examples of non-dominated solution sets. (a) Residential Land-A; (b) Commercial and Business Land-A. Axes x, y, and z represent the three site-scale objectives (i.e., construction cost per unit LID parcel area, water quality score, and reduction rate of runoff volume, respectively). Each point represents an optimized LID-BMP chain. No identical value of the runoff quantity objective (axis z) exists between any two points

Tab.2 Results of block-scale scenario analysis

Fig.5 Scenario comparison of performance in runoff quantity and quality control: (a) Profiles of a certain main pipeline on occurrence of the maximum flow. The top curve depicts the variation of the ground elevation. The second curve is the total water head line that depicts the waterhead distribution. The unit of the waterhead was foot (1ft= 30.48 cm). The rainwater is filled with grey. If the waterline is out of the pipe, the overflow occurs; (b) The control rate of total runoff volume (R_total) and the peak discharge at the pumping station; (c) The pollutant loads into Haihe River and into green corridors

Fig.6 Price/performance ratios of the four LID scenarios with varied weight values of the quantity indices (ω₁) on scenario evaluation and selection. The weight values of the pollutant loads and the construction cost were assumed to be equal (i.e., ω₂=ω₃)

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