Skip to main content

Advertisement

SpringerLink
Log in

Optimization design and research of simulation system for urban green ecological rainwater by genetic algorithm

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

This exploration aims to propose an urban green rainwater management model based on urban green ecological rainwater system (GERS) to solve the problem of urban waterlogging caused by urbanization and realize the local recycling of urban rainwater resources. First, the urban one-dimensional rainwater pipe network model and two-dimensional surface model are implemented based on MIKE URBAN model. Next, a green ecological rainwater facility model is implemented through node generalization to evaluate the rainwater pipe network pressure and land water area. Finally, the improved multi-objective optimization non-dominated sorting genetic algorithms-II (NSGA-II) is used to optimize the design and research of urban green ecological rainwater simulation systems. The results show that compared with traditional genetic algorithms and non-dominated sorting genetic algorithms (NSGA), the accuracy of NSGA-II is 96.17% and 88.57%, which greatly improves the application performance of the algorithm. The effectiveness of the algorithm is verified by comparing the performance of traditional genetic algorithm (GA) and improved sorting GA. The research conclusion is that NSGA-II is superior to the conventional design scheme in economy and hydraulic performance. The above results can provide a reference for using green ecological rainwater model to solve urban rainstorms and flood management in complex terrain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig.12
Fig.13
Fig.14
Fig.15
Fig.16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23

Similar content being viewed by others

References

  1. Hu M, Zhang X, Siu YL, Li Y, Tanaka K, Yang H, Xu Y (2018) Flood mitigation by permeable pavements in Chinese sponge city construction. Water 10(2):172. https://doi.org/10.3390/w10020172

    Article  Google Scholar 

  2. Bell CD, McMillan SK, Clinton SM, Jefferson AJ (2016) Hydrologic response to stormwater control measures in urban watersheds. J Hydrol 541:1488–1500. https://doi.org/10.1016/j.jhydrol.2016.08.049

    Article  Google Scholar 

  3. Chui TFM, Liu X, Zhan W (2016) Assessing cost-effectiveness of specific lid practice designs in response to large storm events. J Hydrol 533:353–364. https://doi.org/10.1016/j.jhydrol.2015.12.011

    Article  Google Scholar 

  4. Cano OM, Barkdoll BD (2017) Multiobjective, socioeconomic, boundary-emanating, nearest distance algorithm for stormwater low-impact BMP selection and placement. J Water Resour Plan Manag. https://doi.org/10.1061/(asce)wr.1943-5452.0000726

    Article  Google Scholar 

  5. Petit-Boix A, Sevigné-Itoiz E, Rojas-Gutierrez LA, Barbassa AP, Josa A, Rieradevall J, Gabarrell X (2017) Floods and consequential life cycle assessment: integrating flood damage into the environmental assessment of stormwater Best Management Practices. Journal of Clean Prod 162:601–608. https://doi.org/10.1016/j.jclepro.2017.06.047

    Article  Google Scholar 

  6. Wang M, Zhang DQ, Su J, Dong JW, Tan SK (2018) Assessing hydrological effects and performance of low impact development practices based on future scenarios modeling. Journal of Clean Prod 179:12–23. https://doi.org/10.1016/j.jclepro.2018.01.096

    Article  Google Scholar 

  7. Firehock K, Walker RA, Firehock K et al (2015) Strategic green infrastructure planning: a multi-scale approach[M]. Island press/center for resource economics, Washington, DC

    Book  Google Scholar 

  8. Lottering N, Plessis DD, Donaldson R (2015) Coping with drought: the experience of water sensitive urban design (WSUD) in the George Municipality. Water SA 41(1):1–7. https://doi.org/10.4314/wsa.v41i1.1

    Article  Google Scholar 

  9. Perales-Momparler S, Andrés-Doménech I, Hernández-Crespo C et al (2016) The role of monitoring sustainable drainage systems for promoting transition towards regenerative urban built environments: a case study in the Valencian region, Spain. Journal of Clean Prod 163:S113–S124. https://doi.org/10.1016/j.jclepro.2016.05.153

    Article  Google Scholar 

  10. Li H, Ding L, Ren M, Li C, Wang H (2017) Sponge City construction in China: a survey of the challenges and opportunities. Water 9(9):594. https://doi.org/10.3390/w9090594

    Article  Google Scholar 

  11. Mollerup AL, Mikkelsen PS, Thornberg D et al (2015) Regulatory control analysis and design for sewer systems. Environ Model Softw 66:153–166. https://doi.org/10.1016/j.envsoft.2014.12.001

    Article  Google Scholar 

  12. Simona SC, Marco M, Irena S (2016) A long-term hydrological modelling of an extensive green roof by means of SWMM. Ecol Eng 95:876–887. https://doi.org/10.1016/j.ecoleng.2016.07.009

    Article  Google Scholar 

  13. Leandro J, Martins R (2016) A methodology for linking 2D overland flow models with the sewer network model SWMM 5.1 based on dynamic link libraries. Water Sci Technol 73(12):3017–3026. https://doi.org/10.2166/wst.2016.171

    Article  Google Scholar 

  14. Koudelak P, West S (2007) Sewerage network modelling in Latvia, use of InfoWorks CS and storm water management model 5 in Liepaja city. Water & Environ J 22(2):81–87. https://doi.org/10.1111/j.1747-6593.2007.00079.x

    Article  Google Scholar 

  15. Zhou QQ (2014) A review of sustainable urban drainage systems considering the climate change and urbanization impacts. Water 6(4):976–992. https://doi.org/10.3390/w6040976

    Article  Google Scholar 

  16. Teng J, Jakeman AJ, Vaze J et al (2017) Flood inundation modelling: a review of methods, recent advances and uncertainty analysis. Environ Model Softw 90:201–216. https://doi.org/10.1016/j.envsoft.2017.01.006

    Article  Google Scholar 

  17. Hu L, Lu W, Zhang ZK (2016) Application of MIKE11 model in water quality early-warning and protection in Dong Tiaoxi water source. Chinese J Hydrodyn, doi: https://doi.org/10.16076/j.cnki.cjhd.2016.01.005

  18. Morianou GG, Kourgialas NN, Karatzas GP et al (2016) Hydraulic and sediment transport simulation of Koiliaris River using the MIKE 21C model. Procedia Eng 162:463–470. https://doi.org/10.1016/j.proeng.2016.11.089

    Article  Google Scholar 

  19. Zhang SH, Pan BZ (2014) An urban storm-inundation simulation method based on GIS. J Hydrol 517:26–268. https://doi.org/10.1016/j.jhydrol.2014.05.044

    Article  Google Scholar 

  20. Bisht DS, Chandranath C, Kalakoti S et al (2016) Modeling urban floods and drainage using SWMM and MIKE URBAN: a case study. Nat Hazards 84(2):749–776. https://doi.org/10.1007/s11069-016-2455-1

    Article  Google Scholar 

  21. Chen XL, Zhao SD, Zhao DQ, Sheng Z (2015) Introduction of digitalwater simulation system. Chinese China Water Wastewater 31(1):104–108

    Google Scholar 

  22. Jia HF, Yao HR, Tang Y, Yu SL, Field R, Tafuri AN (2015) LID-BMPs planning for urban runoff control and the case study in China. J Environ Manage 149:65–76. https://doi.org/10.1016/j.jenvman.2014.10.003

    Article  Google Scholar 

  23. Chang TJ, Wang CH, Chen AS (2015) A novel approach to model dynamic flow interactions between storm sewer system and overland surface for different land covers in urban areas. J Hydrol 524:662–679. https://doi.org/10.1016/j.jhydrol.2015.03.014

    Article  Google Scholar 

  24. Zölch T, Henze L, Keilholz P, Pauleit S (2017) Regulating urban surface runoff through nature-based solutions – an assessment at the micro-scale. Environ Res 157:135–144. https://doi.org/10.1016/j.envres.2017.05.023

    Article  Google Scholar 

  25. Campisano A, Butler D, Ward S et al (2017) Urban rainwater harvesting systems: research, implementation and future perspectives. Water Res 115:195–209. https://doi.org/10.1016/j.watres.2017.02.056

    Article  Google Scholar 

  26. Bashar MZI, Karim MR, Imteaz MA (2018) Reliability and economic analysis of urban rainwater harvesting: a comparative study within six major cities of Bangladesh. Resour Conserv Recycl 133:146–154. https://doi.org/10.1016/j.resconrec.2018.01.025

    Article  Google Scholar 

  27. Zhang S, Zhang J, Yue T et al (2019) Impacts of climate change on urban rainwater harvesting systems. Sci Total Environ 665:262–274. https://doi.org/10.1016/j.scitotenv.2019.02.135

    Article  Google Scholar 

  28. Qin Z, Yao Y, Zhao J et al (2021) Investigation of migration rule of rainwater for sponge city roads under different rainfall intensities. Environ Geochem Health. https://doi.org/10.13616/j.cnki.gcjsysj.2020.03.030

    Article  Google Scholar 

  29. Ranaee E, Abbasi AA, TabatabaeeYazdi J et al (2021) Feasibility of rainwater harvesting and consumption in a middle eastern semiarid urban area. Water 13(15):2130. https://doi.org/10.3390/w13152130

    Article  Google Scholar 

  30. Abebe Y, Kabir G, Tesfamariam S (2018) Assessing urban areas vulnerability to pluvial flooding using GIS applications and Bayesian belief network model. J Clean Prod 174:1629–1641. https://doi.org/10.1016/j.jclepro.2017.11.066

    Article  Google Scholar 

  31. MOHURD (2014) Technical guide of sponge city construction[Z]. Ministry of housing and urban-rural development of the People's Republic of China, Beijing, (in Chinese).

  32. DHI (2016) (Danish Hydraulic Institute). Mike URBAN User Manual[Z]. Danish Hydraulic Institute, Hørsholm, Denmark

  33. Lee KS, Cho WS, Hwang JW et al (2015) Numerical simulation for reducing the flood damage of green park using MIKE URBAN. Int J Control & Autom 8(1):37–54

    Article  Google Scholar 

  34. Artina S, Bolognesi A, Liserra T et al (2007) Simulation of a storm sewer network in industrial area: Comparison between models calibrated through experimental data. Environ Model Softw 22(8):1221–1228

    Article  Google Scholar 

  35. Mark O, Weesakul S, Apirumanekul C et al (2004) Potential and limitations of 1D modelling of urban flooding. J Hydrol 299(3–4):284–299. https://doi.org/10.1016/j.jhydrol.2004.08.014

    Article  Google Scholar 

  36. Duchesne S, Mailhot A, Dequidt E et al (2001) Mathematical modeling of sewers under surcharge for real time control of combined sewer overflows. Urban Water 3(4):241–252. https://doi.org/10.1016/S1462-0758(01)00037-1

    Article  Google Scholar 

  37. León AS, Ghidaoui MS, Schmidt AR et al (2006) Godunov-type solutions for transient flows in sewers. J Hydraul Eng 132(8):800–813. https://doi.org/10.1061/(ASCE)0733-9429(2006)132:8(800)

    Article  Google Scholar 

  38. Ahmed ESMS, Mays LW (2013) Model for determining real-time optimal dam releases during flooding conditions. Nat Hazards 65:1849–1861. https://doi.org/10.1007/s11069-012-0444-6

    Article  Google Scholar 

  39. Schmitt TG, Thomas M, Ettrich N (2004) Analysis and modeling of flooding in urban drainage systems. J Hydrol 299(3–4):300–311. https://doi.org/10.1016/j.jhydrol.2004.08.012

    Article  Google Scholar 

  40. Lin S, Hsieh S, Kuo J et al (2006) Integrating legacy components into a software system for storm sewer simulation. Environ Model Softw 21(8):1129–1140. https://doi.org/10.1016/j.envsoft.2005.05.012

    Article  Google Scholar 

  41. Xie JQ, Chen H, Liao ZL, Gu XY, Zhu DJ, Zhang J (2017) An integrated assessment of urban flooding mitigation strategies for robust decision making. Environ Model Softw 95:143–155. https://doi.org/10.1016/j.envsoft.2017.06.027

    Article  Google Scholar 

  42. Boussaïd I, Lepagnot J, Siarry P (2013) A survey on optimization metaheuristics. Inf Sci 237:82–117. https://doi.org/10.1016/j.ins.2013.02.041

    Article  MathSciNet  MATH  Google Scholar 

  43. Dokeroglu T, Sevinc E, Kucukyilmaz T et al (2019) A survey on new generation metaheuristic algorithms. Comput Ind Eng 137:106040. https://doi.org/10.1016/j.cie.2019.106040

    Article  Google Scholar 

  44. Hussain K, Salleh MNM, Cheng S et al (2019) Metaheuristic research: a comprehensive survey. Artif Intell Rev 52(4):2191–2233. https://doi.org/10.1007/s10462-017-9605-z

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by the Key R & D Project of Shaanxi Province (Project code 2020SF-354) and the Water Conservancy Science and Technology Project of Shaanxi Province (Project code:2015slkj-08). The authors much appreciate the editors and the reviewers for their constructive comments and suggestions which are extremely helpful for improving the paper.

Author information

Authors and Affiliations

  1. School of Water Resources and Electric Power, Xi’an University of Technology, Xi’an, 710048, China

    Lu Cao & Yuling Liu

Authors
  1. Lu Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuling Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuling Liu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, L., Liu, Y. Optimization design and research of simulation system for urban green ecological rainwater by genetic algorithm. J Supercomput 78, 11318–11344 (2022). https://doi.org/10.1007/s11227-021-04192-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-021-04192-7

Keywords

Search

Navigation