China’s Sponge City construction: A discussion on technical approaches

Highlights

Barriers and challenges of Sponge City construction were presented.

Several key technical points on Sponge City implementation were discussed.

Recommendations on Sponge City implementation strategy are proposed.

Abstract

Since 2014, China has been implementing the Sponge City Construction initiative, which represents an enormous and unprecedented effort by any government in the world for achieving urban sustainability. According to preliminary estimates, the total investment on the Sponge City Plan is roughly 100 to 150 million Yuan (RMB) ($15 to $22.5 million) average per square kilometer or 10 Trillion Yuan (RMB) ($1.5 Trillion) for the 657 cities nationwide. The Sponge City Plan (SCP) calls for the use of natural processes such as soil and vegetation as part of the urban runoff control strategy, which is similar to that of low impact development (LID) and green infrastructure (GI) practices being promoted in many parts of the world. The SCP includes as its goals not only effective urban flood control, but also rainwater harvest, water quality improvement and ecological restoration. So far, the SCP implementation has encountered some barriers and challenges due to many factors. The present paper presents a review of those barriers and challenges, offers discussions and recommendations on several technical aspects such as control goals and objectives; planning/design and construction of LID/GI practices; performance evaluation. Several key recommendations are proposed on Sponge City implementation strategy, Site-specific regulatory framework and technical guidance, Product innovation and certification, LID/GI Project financing, LID/GI professional training and certification, public outreach and education. It is expected that the successful implementation of the SCP not only will bring about a sustainable, eco-friendly urbanization process in China, but also contribute enormously to the LID/GI research and development with the vast amount of relevant data and experiences generated from the Sponge City construction projects.

Graphical abstract

Keywords

Low impact development (LID) / Green infrastructure (GI) / Sponge City / Barriers / Construction strategies

References

[1] Jia H, Wang Z, Yu S L. Opportunity and Challenge:China’s Sponge City Plan. Hydrolink, 2016, 4: 100–102

[2] Yu S L, Jia H. China’s ambitious Sponge City initiative: A monumental effort for green/gray infrastructure integration. ASCE EWRI Currents, 2016, 17(4): 8–9

[3] U.S. Environmental Protection Agency (USEPA). Green Infrastructure, 2017. Available at: https://www.epa.gov/green-infrastructure

[4] The CPC Central Committee, The State Council. The National New Urbanization Plan (2014–2020), 2014

[5] The General Office of the State Council. Guiding Opinions on Advancing the Construction of Sponge Cities, 2015

[6] China Ministry of Housing and Urban-Rural Construction (MHURC). Technical guidelines on Sponge City construction—Low impact development stormwater management system, 2014

[7] Jia H, Yao H, Yu S L. Advances in LID BMPs research and practices for urban runoff control in China. Frontiers of Environmental Science & Engineering, 2013, 7(5): 709–720

[8] Torno H C. The Nationwide Urban Runoff Program. In: Proceedings of Proceedings of the Third International Conference on Urban Storm Drainage. Gothenburg, Sweden: Chalmers tekn. hogsk. 1984.

[9] Department of Environmental Resources of Prince George’s County. Low Impact Development Design Strategies: An Integrated Design Approach. Largo, MD: Department of Environmental Resources of Prince George’s County, USA, 1999

[10] Guo C Y. Green concept in stormwater management. Journal of Irrigation and Drainage Systems Engineering, 2013, 2(3): 2168–9768

[11] Roesner L. Hydrology of urban Runoff Quality Management. In: Proceedings of the 18th National Conference on Water Resources, Planning and Management/Symposium on Urban Water Resources, New Orleans, Louisiana, 1991

[12] Brown R A, Hunt W F. Underdrain configuration to enhance bioretention exfiltration to reduce pollutant loads. Journal of Environmental Engineering, 2011, 137(11): 1082–1091

[13] Yu S L, Hamilton P A, Kent C E. Temporal Distribution of Rainfall in Virginia, Final Technical Report to Federal Highway Administration, Virginia Highway and Transportation Research Council, Charlottesville, VA, 1985

[14] Soil Conservation Service (SCS). National Engineering Handbook. Section 4, Hydrology (NEH-4). US Department of Agriculture, Washington, DC., 1985

[15] Jia H F, Lu Y W, Yu S L, Chen Y R. Planning of LID-BMPs for urban runoff control: The case of Beijing Olympic Village. Separation and Purification Technology, 2012, 84: 112–119

[16] Zhen X Y, Yu S L, Lin J Y. Optimal location and sizing of stormwater basins at watershed scale. Journal of Water Resources Planning and Management, 2004, 130(4): 339–347

[17] Maryland Department of Environment (MDE). Stormwater Management Manual, Maryland DOE, USA, 2009. Available at: http://www.mde.state.md.us

[18] Jia H, Yao H, Tang Y, Yu S L, Zhen J X, Lu Y. Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection. Environmental Monitoring and Assessment, 2013, 185(9): 7915–7933

[19] Jia H, Yao H, Tang Y, Yu S L, Field R, Tafuri A N. LID-BMPs planning for urban runoff control and the case study in China. Journal of Environmental Management, 2015, 149(1): 65–76

[20] Cheng M S, Zhen J X, Shoemaker L. BMP decision support system for evaluating stormwater management alternatives. Frontiers of Environmental Science & Engineering, 2009, 3(4): 453–463

[21] Xu T, Jia H F, Wang Z, Mao X H, Xu C Q. SWMM-based methodology for block-scale LID-BMPs planning based on site-scale multi-objective optimization: A case study in Tianjin. Frontiers of Environmental Science & Engineering, 2017, 11: 1 doi:10.1007/s11783-017-0934-6

[22] USEPA. Urban Stormwater BMP Performance Monitoring: A Guidance Manual for Meeting the National Stormwater BMP Database Requirements. 2002, EPA-821-B-02–001.

[23] Zhang R, Zhou W, Field R, Tafuri A, Yu S L, Jin K. Field test of best management practice pollutant removal efficiencies in Shenzhen, China. Frontiers of Environmental Science & Engineering, 2009, 3(3): 354–363

[24] Jia H, Wang X, Ti C, Zhai Y, Field R, Tafuri A N, Cai H, Yu S L. Field monitoring of a LID-BMP treatment train system in China. Environmental Monitoring and Assessment, 2015, 187(6): 373

[25] Qin H P, Li Z X, Fu G. The effects of low impact development on urban flooding under different rainfall characteristics. Journal of Environmental Management, 2013, 129: 577–585

[26] Wu J, Yu S L, Zou R. Water quality-based BMP implementation approach for efficient nonpoint source pollution control. Journal of the American Water Resources Association, JAWRA., 2006, 42(5): 1193–1204

[27] U.S. Environmental Protection Agency (USEPA). Laws & Regulations, 2017. Available at: https://www.epa.gov/laws-regulations/regulations

[28] Jia H F, Ma H T, Sun Z X, Yu S L, Ding Y W, Liang Y. A closed urban scenic river system using stormwater treated with LID-BMP technology in a revitalized historical district in China. Ecological Engineering, 2014, 71: 448–457

[29] Xu C Q, Hong J L, Jia H F, Liang S D, Xu T. Life cycle environmental and economic assessment of a LID-BMP treatment train system: A case study in China. Journal of Cleaner Production, 2017, 149: 227–237

[30] Mao X H, Jia H F, Yu S L. Assessing the ecological benefits of aggregate LID-BMPs through modelling. Ecological Modelling, 2017, 353: 139–149

[31] Han Y, Jia H F. Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China. Ecological Modelling, 2017, 353: 107–116

[32] Jia H F, Wang S, Wei M J, Zhang Y. Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model. Frontiers of Environmental Science & Engineering in China, 2011, 5(2): 255–265 doi:10.1007/s11783-010-0279-x

[33] Boyd J, New Face of the Clean Water Act: A Critical Review of the EPA's New TMDL Rules. 11 Duke Environmental Law & Policy Forum, 2000, 39–87

[34] Liang S, Jia H, Yang C, Melching C, Yuan Y. A pollutant load hierarchical allocation method integrated in an environmental capacity management system for Zhushan Bay, Taihu Lake. Journal: Science of the Total Environment, 2015, 533: 223–237

[35] Guo Y, Jia H F. An approach to calculating allowable watershed pollutant loads. Frontiers of Environmental Science & Engineering, 2012, 6(5): 658–671

[36] USEPA. Getting Certified by EPA, 2017. Available at: https://www.epa.gov/home/getting-certified-epa

[37] Prince George’s County. Maryland, USA. The Prince George’s County 3P Green Infrastructure Implementation Program, 2017. Available at: https://thecleanwaterpartnership.com

Acknowledgements

We gratefully acknowledge financial support from the Beijing Natural Science Foundation Project (No. 8161003), Natural Science Foundation Project (No. 51278267), and the National Water Pollution Control Special Project (No. 2011ZX07301-003). Several points and the contents in the manuscript are discussed with many experts during 2016 International Low Impact Conference in Beijing.

RIGHTS & PERMISSIONS

2017 Higher Education Press and Springer–Verlag Berlin Heidelberg